Emergent Climate Phenomena

In a recent post, I described how the El Nino/La Nina alteration operates as a giant pump. Whenever the Pacific Ocean gets too warm across its surface, the Nino/Nina pump kicks in and removes the warm water from the Pacific, pumping it first west and thence poleward. I also wrote about the dolphins in a piece called “Here There Be Dragons“.

Fulfilling an obligation I incurred in the latter paper by saying I would write about emergence and climate, let me take a larger overview of the situation by noting that both the El Nino pump and the dolphins are examples of a special class of things that are called “emergent” phenomena.

Figure 1. Hands emerging from the paper …

Emergence is a very important concept. Systems with emergent phenomena operate under radically different rules than those without. Today I want to talk about emergent systems, and why they need to be analyzed in different ways than systems which do not contain emergent phenomena.

Examples of natural emergent phenomena with which we are familiar include sand dunes, the behavior of flocks of birds, vortexes of all kinds, termite mounds, consciousness, and indeed, life itself. Familiar emergent climate phenomena include thunderstorms, tornadoes, clouds, cyclones, El Ninos, and dust devils.

Generally speaking, we recognize emergent phenomena because they surprise us. By that, I mean emergent phenomena are those which are not readily predictable from the underlying configuration and physics of the situation. Looking at a termite, if you didn’t know about their mounds there’s no way you’d say “I bet these bugs build highly complex structures a thousand times taller than they are, with special air passages designed to keep them cool”. You wouldn’t predict mounds from looking at termites, no way. They are an emergent phenomenon.

The El Nino phenomenon is another excellent example of emergent phenomena. Looking at a basin of water like the Pacific, there’s no way you would say “Hey, I’ll bet that ocean has this complex natural system that kicks in whenever the ocean overheats, and pumps warm water up to the poles.” You wouldn’t predict the existence of the El Nino from the existence of the Pacific Ocean. It also is an emergent phenomenon.

In addition to their surprising emergence from the background, what other characteristics do emergent phenomena possess to allow us to tell them from other non-emergent phenomena?

One common property of emergent phenomena is that they are flow systems which are far from equilibrium. As a result, they need to evolve and change in order to survive. They are mobile and mutable, not fixed and unchanging. And locally (but of course not globally) they can reverse entropy (organize the local environment). Indeed, another name for emergent phenomena is “self-organized phenomena”.

Another key to recognizing emergent phenomena is that they arise spontaneously when conditions are right. They don’t have to be artificially generated. They create themselves in response to external stimuli.

Next, they often have a lifespan. By a “lifespan”, I mean that they come into existence at a certain time and place, often when some natural threshold is exceeded. Thereafter they are in continuous existence for a certain length of time, and at the end of that time, they dissipate or disappear.

Another characteristic of emergent phenomena is that they are not cyclical, or are at best pseudo-cyclical. They do not repeat or move in any regular or ordered or repetitive fashion. Often they can move about independently, and when they can do so, their movements can be very hard to predict.

Another feature of emergent phenomena is that they are often threshold-based. By that I mean that they rarely emerge below that threshold, but above it their numbers increase rapidly.

Another attribute of emergent systems is that they are often associated with phase changes in the relevant fluids, e.g. clouds occur because of a phase change of water.

One final attribute of threshold-based emergent systems is crucial to this discussion—they exhibit “overshoot” or hysteresis. In the Rayleigh-Bénard circulation shown below, it takes a certain threshold temperature difference from top to bottom to cause the emergence of the circulation pattern. But once that circulation is established, it will persist even though you turn the heat down far below the initiation threshold temperature.

So those are some of the characteristic features of emergent phenomena. They are flow systems far from equilibrium which arise spontaneously, often upon crossing a critical threshold. They are not obviously predictable from the underlying conditions. They move and act unpredictably, they are often associated with phase changes, and they exhibit “overshoot” (hysteresis).

However, not all emergent systems are created equal. Some of them are what might be termed “field-wide”. An example of this is the spontaneous emergence of “Rayleigh-Bénard” natural circulation in a fluid heated from the bottom and cooled from the top.

Figure 2. Rayleigh-Bénard circulation. Curiously, the time reads first down the right column then down the left. At the end an organized series of rising and falling areas is emerging. It is characterized by narrower rapidly upwelling sections, separated by larger, slower-moving downwelling sections. Original Caption: Onset and development of thermal convection cells in Rayleigh-Benard convection. Note the regularity of initial “bubbles” and their coalescence to form larger loops. SOURCE

Another, more complex type of emergent systems are what might be called “independent”. Examples of these in the climate world are thunderstorms and dust devils. Unlike the field-wide emergent phenomena, these are free to roam about the landscape. Like all flow systems far from equilibrium, they are constantly adjusting and evolving to met the physical constraints. For example, thunderstorms move preferentially across the surface to warmer areas.

As I said above, I want to highlight the difference between the analysis of systems that do and do not contain emergent phenomena. My thesis is that systems with emergent phenomena cannot be analyzed in the same manner as systems without emergent phenomena. The corollary is that climate models are appropriate only for systems without emergent phenomena. Let me give an example of each kind of system, so you can see the difference.

For the first system, let me consider a flat slab of iron that is warmed by the sun or some other heat source in a vacuum. As the heat source varies, the temperature of the slab of iron varies as well. This variation in temperature with energy input is quite regular and predictable. If we graph the changes, we’d see that there are no sharp bends in the graph. In addition, the more energy that the iron is receiving, the hotter it gets, with an unchanging mathematical relationship between downwelling radiation and the temperature of the iron slab. So we could approximate it by a straight line.

Now, lets replace the flat slab of iron with a flat slab of cool water, and we’ll add the possibility of clouds and thunderstorms as the emergent phenomena. Starting with cool water, at first we’d see basically the same thing as with the iron slab—the more energy we add, the warmer the water gets. Everything is all nicely proportional, the water is acting just like the iron. (Yes, there’s a million details, but work with me here. It’s a thought experiment.)

But at a certain point, a curious and surprising thing happens. A threshold is passed, and clouds form.And when they do, it reflects some of the incoming energy back to space. So we get a “knuckle” in the graph of incoming energy versus temperature. We’re no longer warming as fast as we were.

If the incoming energy continues to rise, however, a more surprising thing happens. Another threshold is passed, and thunderstorms begin to form. These cool the surface in a host of ways, most importantly by piping the warm surface air through the middle of the thunderstorm up to high altitudes. This avoids almost all of the greenhouse gases (H2O and CO2) in the lower troposphere, and allows for free radiation of huge amounts of thermal energy to space. Not only that, but thunderstorms are radically different from a feedback, because they cool the surface down to well below the thunderstorm initiation threshold temperature. This means that they can not only slow down a temperature increase, they can stop it in its tracks.

And at that point, when thunderstorms start forming, the water basically stops warming. Further increases in incoming energy are simply equalled by further increases in thunderstorms and changes in their orientation, so that the surface temperature hardly warms after that.

Now, one of the claims of the AGW supporters is that there is a linear relationship between downwelling energy and temperature. They say that any increase in incoming energy must be matched by an increase in surface temperature. Despite the known non-linearity of the system, the claim is made that over a narrow interval, a linear approximation of the relationship between energy and temperature is a very reasonable approximation to the reality.

But in the thunderstorm part of the tropical thermal regime, it is important to note that not only is the relationship between incoming energy and temperature non-linear, but in fact there is no relationship between incoming energy and temperature. So you cannot even approximate it with a linear relationship. In that regime, increases in incoming energy are generally balanced out by increases in thunderstorm numbers and associated increased evaporation and convection, leaving only small residual temperature changes.

So one reason you can’t simply map a linear approximation to a non-linear relationship is because in the thunderstorm regime, there is almost no relationship, non-linear or otherwise, between incoming energy and temperature. Given the number of phase changes of water that are involved in the thunderstorm system, this should be no surprise at all—the same exact situation occurs when water is boiling. The temperature of the boiling water can no longer be even approximated by looking at how much energy is going into the water. The boiling water system simply moves energy through it at a faster rate, it doesn’t run any hotter. The exact same thing is going on in the thunderstorm regime. If you increase the solar radiation, all you get is more thunderstorms moving faster. The surface doesn’t get hotter, the energy and the water just circulate faster.

There is a second reason that you can’t just take an average, note that the average doesn’t move much, and assume linearity. The problem is that in the tropics, the climate sensitivity is very different depending on the time of day. Here’s why. First, without reference to anything else, climate sensitivity is an inversely proportional function of temperature for several reasons.

• Radiation is a function of T^4.

• Parasitic losses increase with temperature.

• Emergent cooling mechanisms (thunderstorms, dust devils, rain) are temperature based with high numbers above a threshold of emergence.

So clearly, climate sensitivity is inversely proportional to temperature, falling as temperature rises. It is not a constant in any sense of the word.

Next, climate sensitivity varies over both space and time. In the early morning in the all-critical tropics where the energy enters the planet-sized heat engine we call “climate”, the temperature rises rapidly because of the lack of clouds—a high change in temperature per change in watts (high sensitivity). In the late morning the watts are still rising but the clouds greatly reduce the temperature rise—smaller change in temperature per change in watts (low sensitivity). And indeed, certain areas at certain times can show negative sensitivity, and some areas of the planet are not sensitive to the forcing at all.

Now, the global average climate sensitivity, the one that people take as a constant, is no more than the average of these highly varying sensitivities. But the average is greatly misleading, because it is taken as constant or semi-constant. In the real world, however, climate sensitivity not constant in any sense. It is both inversely proportional to temperature and highly non-linear.

For example, in Figure 3 above, the “climate sensitivity” is taken as the average slope of the linear trend line relating temperature and incoming radiation. As you can see, if the earth were like an iron slab with no emergent phenomena, a straight light approximates the curve extremely well at every temperature. But in the real world with water and clouds, the trend line is meaningless—it doesn’t represent the actual climate sensitivity at any temperature.

As a result you can’t just say well, because the global average surface temperature doesn’t vary much, we can treat it as a constant. The average is not real, it is a mathematical chimera. In the real world, we don’t see an average temperature. If the “average temperature” goes up by one degree, and it happens to be evenly spread out, let’s say the morning temperature goes from say 7°C to 8°C, while the afternoon goes from 22°C to 23°C.

But both the climate sensitivity, and the change in climate sensitivity with temperature, are very, very different in the two temperature regimes of morning and afternoon. It takes much, much more energy to go from 22°C to 23°C than it does to go from 7°C to 8°C. So while the average temperature doesn’t change much, that is highly deceptive. In reality, the dependence of sensitivity on temperature makes a huge difference in how the system actually reacts to changes in forcing.

To explain this in detail, I’m going to shamelessly steal, re-heat, and re-forge a section from my earlier post called “It’s Not About Feedback”, because it is highly relevant to the questions I’m discussing. To understand why emergent phenomena are critical to understanding the climate, here is the evolution of the day and night in the tropical ocean. The tropical ocean is where the majority of the sun’s energy enters the huge heat engine we call the climate. So naturally, it is also where the major homeostatic mechanism are located.

At dawn, the atmosphere is stratified, with the coolest air nearest the surface. The nocturnal overturning of the ocean is coming to an end. The sun is free to heat the ocean. The air near the surface eddies randomly.

Figure 4. Average conditions over the tropical ocean shortly after dawn.

As you can see, there are no emergent phenomena in this regime. Looking at this peaceful scene, you wouldn’t guess that you could be struck by lightning in a few hours … emergence roolz. As the sun continues to heat the ocean, around ten or eleven o’clock in the morning there is a sudden regime shift. A new circulation pattern replaces the random eddying. As soon as a critical temperature/humidity threshold is passed, local circulation cells spring up everywhere. These cells transport water vapor upwards to the local lifting condensation level. At that level, the water vapor condenses into clouds as shown in Figure 3.

Figure 5. Average conditions over the tropical ocean when cumulus threshold is passed.

Note that this area-wide shift to an organized circulation pattern is not a change in feedback. It has nothing to do with feedback. It is a self-organized emergent phenomenon. It is threshold-based, meaning that it emerges spontaneously when a certain threshold is passed. In the “wet” deep tropics there’s plenty of water vapor, so the major variable in the threshold is the temperature. In addition, note that there are actually two distinct emergent phenomena in the drawing, the Rayleigh-Bénard circulation which emerges prior to the cumulus formation, and which is enhanced and strengthened by the emergence of the clouds.

Note also that we now have a change of state involved as well, with evaporation from the surface and condensation and re-evaporation at altitude.

Under this new late-morning cumulus circulation regime, much less surface warming goes on. Part of the sunlight is reflected back to space, so less energy makes it into the system to begin with. Then the increasing surface wind due to the cumulus-based circulation pattern increases the evaporation, reducing the surface warming even more by moving latent energy up to the lifting condensation level.

Note that the system is self-controlling. If the ocean is a bit warmer, the new circulation regime starts earlier in the morning, and cuts down the total daily warming. On the other hand, if the ocean is cooler than usual, clear morning skies last later into the day, allowing increased warming. The system is regulated by the time of onset of the regime change.

Let’s stop at this point in our examination of the tropical day and consider the idea of “climate sensitivity”. The solar forcing is constantly increasing as the sun rises higher in the sky. In the morning before the onset of cumulus circulation, the sun comes through the clear atmosphere and rapidly warms the surface. So the thermal response is large, and the climate sensitivity is high.

After the onset of the cumulus regime, on the other hand, much of the sunlight is reflected back to space. Less sunlight remains to warm the ocean. In addition to reduced sunlight there is enhanced evaporative cooling. Compared to the morning, the climate sensitivity is much lower. The heating of the surface slows down.

So here we have two situations with very different climate sensitivities. In the early morning, climate sensitivity is high, and the temperature rises quickly with the increasing solar insolation. In the late morning, a regime change occurs to a situation with much lower climate sensitivity. Adding extra solar energy doesn’t raise the temperature anywhere near as fast as it did earlier.

Moving along through the day, at some point in the afternoon there is a good chance that the cumulus circulation pattern is not enough to stop the continued surface temperature increase. When the temperature exceeds a certain higher threshold, another complete regime shift takes place. Some of the innocent cumulus clouds suddenly mutate and grow rapidly into towering monsters. The regime shift involves the spontaneous generation of those magical, independently mobile heat engines called thunderstorms.

Thunderstorms are dual-fuel heat engines. They run on low-density air. That air rises and condenses out the moisture. The condensation releases heat that re-warms the air, which rises deep into the troposphere.

Figure 6. Afternoon thunderstorm circulation over the tropical ocean.

There are a couple of ways to get low density air. One is to heat the air. This is how a thunderstorm gets started, as a strong cumulus cloud. The sun plus GHG radiation combine to heat the surface, warming the air. The low density air rises. When that gets strong enough, a thunderstorm starts to form.

Once the thunderstorm is started, the second fuel is added to the fire — water vapor. Counter-intuitively, the more water vapor there is in the air, the lighter it becomes. The thunderstorm generates strong winds around its base. Evaporation is proportional to wind speed, so this greatly increases the local evaporation.

This, of course, makes the air lighter, and makes the air rise faster, which makes the thunderstorm stronger, which in turn increases the wind speed around the thunderstorm base, which increases the evaporation even more … a thunderstorm is a regenerative system, much like a fire where part of the energy is used to run a bellows to make the fire burn even hotter. Once it is started, it is much harder to stop.

This gives thunderstorms a unique ability that, as far as I know, is not represented in any of the climate models. It is capable of driving the surface temperature well below the temperature that was needed to get it going. It can run on into the evening, and at times well into the night, on its combination of thermal and evaporation energy sources.

Thunderstorms can be thought of as local leakages that transport heat rapidly from the surface to the upper atmosphere. They cool the surface in a host of ways, utilizing a combination of cold water, shade, wind, spray, evaporation, albedo changes and cold air.

And just like the onset of the cumulus circulation, the onset of thunderstorms occurs earlier on days when it is warmer, and it occurs later (and sometimes not at all) on days that are cooler than usual.

So again, we see that there is no way to assign an average climate sensitivity. The warmer it gets, the less each additional watt per metre actually warms the surface.

Finally, once all of the fireworks of the daytime changes are over, first the cumulus and then the thunderstorms decay and dissipate. A final and again different regime ensues. The main feature of this regime is that during this time, the ocean radiates about the amount of the energy that it absorbed during all of the previously described regimes. How does it do this? Another emergent phenomenon …

Figure 8. Conditions prevailing after the night-time dissipation of the daytime clouds.

During the nighttime, the surface is still receiving energy from the GHGs. This has the effect of delaying the onset of oceanic overturning, and of reducing the rate of cooling. Note that the oceanic overturning is once again the emergent Rayleigh-Bénard circulation. Because there are no clouds, the ocean can radiate to space more freely. In addition, the overturning of the ocean constantly brings new water to the surface, to radiate and to cool. This increases the heat transfer across the interface.

As with the previous thresholds, the timing of this final transition is temperature dependent. Once a critical threshold is passed, oceanic overturning kicks in. Stratification is replaced by circulation, bringing new water to radiate, cool, and sink. In this way, heat is removed, not just from the surface as during the day, but from the entire body of the upper layer of the ocean.

There are a few things worth pointing out about this whole system.

First, this is what occurs in the tropics, which is where the energy enters the hot end of the great heat engine we call the climate.

Next, sometimes increases in incoming energy are turned mostly into temperature. Other times, incoming energy increases are turned mostly into physical work (the circulation of the ocean and atmosphere that transports energy to the poles). And other times, increasing energy is mostly just moved from the tropics to the poles.

Next, note that this whole series of changes is totally and completely dependent on temperature threshold based emergent phenomena. It is a mistake to think of these as being feedback. It’s more a drunk walking on a narrow walkway, the guardrails are not feedback—they are a place where the rules change. The various thresholds in the climate system are like that—when you cross them, everything changes. The ocean before and after the onset of overturning are very different places.

And this, in turn, all points to one of the most important control features of the climate—time of onset. How much energy the ocean loses overnight depends critically on what time the overturning starts. The temperature of the tropical afternoon depends on what time the cumulus kick in, and what time the thunderstorms start

Finally, look at the difficulty in analyzing or modeling this kind of situation. You have a grid box that is far larger than any cloud or thunderstorm. And all you have to go on, the only things in your model, are the average statistics of that gridbox. And the main control system is the timing of the initiation of threshold based phenomena that are below your gridcell size …

Think about say the average humidity of the tropical Pacific where there are thunderstorms. As soon as the thunderstorms kick in, they start discharging dry air up high. This dry air cools and descends in the area between the thunderstorms. So if you were to average the relative humidity of the bulk of the atmosphere across say one gridcell of a climate model, a hundred miles square or so, you’d see humidity falling as thunderstorms develop.

But this bulk drying of the downwelling air masks what is really happening. Under the thunderstorms, the storm-driven winds kick the evaporation into overdrive. The dry surrounding air is drawn in, loaded to the brim with moisture via the increased evaporation, and shot skyward at rates up to 10 m/sec. In a few minutes it’s moved up to the LCL, the “lifting condensation level”, where it condenses as clouds and rain.

As a result, despite the fact that the bulk atmosphere is drying, in fact huge amounts of moisture are being moved vertically through the system. So simple averages are useless. The system is moving more water but the average relative humidity of the bulk atmosphere has dropped.

So increasing input may only increase the throughput, rather than increasing the temperature. Not all of the energy that hits the tropical ocean is immediately radiated back to space. A large amount of it is moved, via the ocean and the atmosphere, towards the polar regions before finally returning to space. This means that one of the crucial determinants of the temperature of the tropical regions, as well as of the polar regions, is the rate of energy throughput—how much energy is moved from the tropics to the poles. Once the system is into the thunderstorm regime, almost all of the incoming energy goes to simply turning the wheel faster, moving more energy from the surface to the upper troposphere, moving more air and water from the tropics to the polar regions. So instead of warming up the surface, the energy is moved skywards and polewards.

Again, however, these changes in throughput make the situation difficult to analyze. The dang system won’t ever stand still, it responds to everything that happens. How can one accurately measure how much energy is being moved and transformed by a thunderstorm?

An allied difficulty is with the size of the phenomena. The thunderstorm is the most common natural heat engine on the surface of the planet. But they are way, way below the typical grid size of a climate model. As a result, they simply cannot be simulated in modern global climate models. This means that they must be “parametrized”, which as near as I can tell comes from the Latin and means “made up to fit the programmer’s preconceptions”. But while parametrizing a simple system is not difficult, parametrizing a system containing emergent phenomena is a very hard thing to do well.

In part, this problem arises from the very thing causing the need to parameterize—the small size of the thunderstorms. The problem is that those small thunderstorms cool down small hot spots before they ever get large. I have seen, for example, a single solitary thunderstorm in the morning, sitting over some warm spot in the ocean, with not another cloud in the sky. It was feeding off of some very local hot spot which had persisted through the night, and as long as it was hot, the thunderstorm stayed and cooled it down.

How on earth can one parametrize such an instantaneous response to excess warmth? Thunderstorms spring up over hot spots and cool them down to below the initiation temperature of the thunderstorm. And that kind of quick proactive response containing overshoot is not easily put into parameters.

And given that all you have are grid box averages, how will you model the critical changes in the time of onset of the various emergent phenomena? If the cumulus doesn’t appear until an hour later, or shows up an hour earlier, it makes a huge difference. And of course, the clouds and thunderstorms never shows up off-time, it emerges only as and when required, because its appearance is set by the immutable laws of wind and water and evaporation and condensation. It can’t occur late or early, it’s always right on time. But in the models, there are no thunderstorms …

As I mentioned above, there are a range of emergent climate phenomena. In general, they work together to maintain the temperature of the planet within fairly narrow bounds. The most important one of these is the tropical thunderstorm system described above. And there is something very critical about this system, something you may not have noticed so let me repeat it. A main control on the temperature is exerted by the timing and strength of the emergent phenomena, particularly clouds and thunderstorms. Now, here’s the important part. The time of day when a cloud forms is a function of the physics ruling the winds and the waves and the water and evaporation and condensation and the air and how they react to temperature.

Here’s why that statement is important. It is important because of what is missing—there is no mention of CO2, because CO2 doesn’t exert any direct effect on when clouds form. Clouds form in response to temperature and pressure and the like, not CO2.

So if there is a bit of additional forcing and the surface is a bit warm, the clouds simply form earlier, and the thunderstorms form earlier, and the nightly overturning of the ocean starts earlier … and that balances out the additional forcing, just like it has done for millions of years.

Nor is this just theory. I’ve shown that at the TAO buoys, days that start out colder than average end up warmer than average, and days that start out colder end up warmer … just as this theory predicts. See here and here for further discussion of the effect of emergent systems as seen in the TAO buoy records.

Now, note that I didn’t say that this kind of system containing emergent temperature control systems was impossible to model … just that it is hard. I’ve done a lot of computer modeling myself, both iterative and non-iterative models, and so I’ve both written and used physics based models, economic models, models using neural nets, machine learning algorithms, computerized evolution models, tidal models, I’ve played the game a lot in a lot of fields and a lot of ways. It could be done. But it can’t be done the way that they are doing it, because their way doesn’t account for the emergent phenomena.

The emergence of clouds and thunderstorms radically cooling the surface, plus the increase in convection and evaporation with temperature, plus the thermal radiation going up as the fourth power of the temperature, all combine to put a serious barrier in the way of any increases in temperature. As near as I can tell, the climate models have no such barrier. In the model world, going up six degrees or even ten degrees seems to be no big deal, model runs achieve that without breaking a sweat.

But in the real world, of course, Murphy conspires with nature to make sure that every single additional degree is harder and harder to achieve … and emergent phenomena not only stop warming, they actively cool the surface down. Until both the theory and the models robustly embrace the emergent phenomena, the models will continue to be a funhouse-mirror version of reality … you can recognize it as some kind of climate but with all the distortions, you can’t use that as a guide for anything.

One last question—how would I recognize a good climate model? Well, in a good model all of the emergent phenomena we know about would actually emerge, not be parametrized … because the free actions of those emergent phenomena, the variations and changes in their times and locations of appearance are what control the temperature, not the CO2 “control knob”. So when the forcing from CO2 increases a watt or two, in an accurate model the clouds will emerge a few minutes earlier on average across the tropics, and the balance will be restored. This system of control by emergent phenomena has worked very well for billions of years, and it handles large swings in radiation every single day—it won’t be altered by a few watts of extra forcing from CO2.

151 thoughts on “Emergent Climate Phenomena”

” This system of control by emergent phenomena has worked very well for billions of years, and it handles large swings in radiation every single day—it won’t be altered by a few watts of extra forcing from CO2″

Climate science is way way behind you Willis. Their ‘model’ of radiative balance is not real, in that it is a static model. I was amazed to see a professor giving this stilted view of the world to university students. I had to laugh, as it was just plain silly. The world is not only dynamic, but within bounds it is chaotic. You do a great job of describing its essential features.

“Nor is this just theory. I’ve shown that at the TAO buoys, days that start out colder than average end up warmer than average, and days that start out colder end up warmer … just as this theory predicts.”

Did you mean the inverse warmer/colder during the second part of the statement?

Oh, and there’s also hurricanes… One giant thunderstorm is more efficient than a thousand tiny ones.

While I certainly couldn’t have written this paper, I can grasp its broad points. I have felt all along that the complexity of the climate was being grossly underestimated (or more probably under reported) by the CAGW crowd.
Anytime you see simple (especially linear) relationships being insisted on to describe complex, chaotic systems you should be suspicious of the person trying to sell them.
I don’t think that the destruction of our complex society will be accomplished by evil people (although they do exist) but primarily by stupid people that demand easy answers to very hard questions.
Science (as an quasi-institution) has lost its way, preferring to sell its soul for more grant money in return for the simplistic solutions stupid people want and need rather than insisting that having an opinion on some issues (such as climate) requires a lot of study and thought.
Thanks for trying to educate those of us that really want to understand (even if we never quite get it).

“Human being says: “It never rains but it pours.” This is not very apt, for it frequently does rain without pouring. The rabbits proverb is better expressed. They say, “One cloud feels lonely”: and indeed it is true that the appearance of a single cloud often means that the sky will soon be overcast. However that may be, the very next day provided a dramatic second opportunity to put Hazel’s idea into practice”

This essay is the most brilliant, interesting, and important essay in climate science that I have seen in years. Willis does not directly address scientific method but you can see it at work throughout his essay. The best thing about this essay is that it teaches the proper humility that must be shown by anyone who would make claims about climate sensitivity and who would anchor those claims in the facts, the myriad natural processes, that determine earth’s responses to the sun’s radiation.

Nicely put, Willis. I have frequently had severe doubts about the use of averages and this clarifies my thinking. It is rather like taking the average speed of the piston in a pump and saying that because the average speed is zero then the pump cannot work. Finer detail is needed than the gross averages used in the GCMs to tease any useful information out of them.

p.s. How do the climate investigators relate energy to temperature i.e. x downwelling watts gives y temperature change, when every substance has its own specific heat. Change the substance slightly (such as the absolute humidity of the air) and the specific heat also changes. Dry air temperature rises more rapidly for a change in incoming energy than does moist air temperature.

p.p.s. Regarding adjusted (homogenised etc.) data. When I was at school many centuries ago data was what was observed. When any manipulation was done to the data it ceased to be data and become either information or a result. For example, when a solution of NaOH was standardised against potassium hydrogen pthalate the data points were:
1.. the mass of potassium hydrogen pthalate measured (i.e. observed accurately) with a balance.
2.. the volume of NaOH solution measured in a burette.
After the necessary calculations were performed one had a result (the concentration of the solution of NAOH) which was useful information for further analyses.

… the models do not emulate ENSO which is an emergent property of the climate system. Therefore, if ENSO is a significant climatic effect then the failure of the models to emulate it demonstrates the models do not emulate the climate system of the real Earth. In other words, the models are useless for ‘projecting’ the climate of the real Earth.

One aspect of thunderstorms that you don’t cover is that in the humid tropics, once they develop they often persist overnight and into the next day. In Singapore, they are called Sumatras, as they originate over the island of Sumatra and typically reach Singapore late in the night to around dawn.

My experience of Singapore and the Riau islands (within 100km of the equator) is that it rains at all hours of the day and night and there is no noticeable late afternoon rainfall peak. I tried to find a reference but couldn’t. Presumably no one has studied this. I’ll suggest the regime you describe occurs where humidity levels are somewhat lower than the high humidity levels close to the equator.

Despite being pretty familiar with emergent behavior(and thus enjoyed the article immensely) I am mot sure I follow exactly the argument here. You refer to climate sensitivity becomes higher or lower based on the emergent cloud cover. Presumably the sensitivity you are referring to is changes in the incoming solar radiation that was heating the oceans. How though does this apply to sensitivity with respect to CO2 as a GHG? I am not sure we can just correlate the two here.

Despite that discrepancy, anyone who understands non-linear dynamic systems and complexity theory would appreciate that talking about global averages or predicting behavior based on tweaking a variable like CO2 is talking out their ass. All they have to go on is the data, and the data don’t fit.

Well done, Willis, except for the El Nino you do not understand. I learnt a lot. We all knew their models were no good and now we know some more of the reasons for it. And your “Here Be Dragons” is a masterpiece. It should be in some print medium. By the way, once I put you on a cc list for stuff I sent out but that email address from the islands does not work. Arno

“And of course, the clouds and thunderstorms never shows up off-time, it emerges only as and when required, because its appearance is set by the immutable laws of wind and water and evaporation and condensation. It can’t occur late or early, it’s always right on time.”

Frodo: “You’re late.”
Gandalf: “A wizard is never late, Frodo Baggins. Nor is he early. He arrives precisely when he means to.”

— “The Fellowship of the Ring”

Also the answer to the riddle, “Why is a wizard like a thunderstorm?” :-)

Emergent line of dolphins? Phooey denier! For starters our time lapse camera at LatitudeX Longtitude Y on Beebopaloola atoll clearly shows sea monsters regularly on the horizon and they’re getting more prolific and threaten to overwhelm us all folks. This network of carefully selected time lapse cameras backs up past proxy sightings from a plethora of interviewed witch doctors that the Royal Society of Sea Monster Watchers have fed so diligently into our computer models. The science is settled and don’t pander to these unqualified cranks and dreamers.

A climate E=mc^2 moment!! This is the most compelling presentation of what is really going on in climate and it doesn’t match anything we are getting from climate scientists. From the contrast, I imagine choice of climate science as a discipline has, to a large number of the experts, been through a belief that it is simple work – linear stuff attracts linear thinkers. You have shown that a highly complex goings-on can be explained convincingly by a real master thinker-educator. I’m proud to say I was here for this. The engineer in me says this is what its all about. Unfortunately instead of being heaped with prizes and honors, you should prepare for abuse – you are a lightning and lightening rod.

Thank you Willis. Would it be correct, then, to summarise by saying: “the system should never experience runaway variation (be it warming or cooling) because emergent climate events will take place to regulate it”?

u.k.(us) says:
February 7, 2013 at 3:44 pm
The Willis I know, did not write this post, so who did ?
================
Never read (only skimmed) past the 3rd paragraph, Willis might have sent it, but he didn’t write it.
It has no “flair”, it reads like a tech seminar.
Writing has style, this has none.

Thank you Willis. Would it be correct, then, to summarise by saying: “the system should never experience runaway variation (be it warming or cooling) because emergent climate events will take place to regulate it”?

The climate system is chaotic and displays bistability (i.e. it seems to be stable in either glacial or interglacial conditions, and it ‘switches’ between these two conditions). Such behaviour is typical of chaotic systems with strange attractors. The emergent properties of the system are probably what holds the system close to either of its two apparently stable states.

It gave me a chuckle to note that we are unlikely to see an avalanche of comments on this article today or on any other day. And so be it; such things are better appreciated in peace in quiet, which I will only break for a moment to give my thanks.

It is an absolutely awesome piece of work, on many levels. To talk about a subject so big without losing track or getting drowned in details, and to arrive at any sort of conclusion in such a short time, having sufficiently covered all the essentials, is a remarkable feat. I see echoes of Prigogine and friends in your observations, but none of those guys were as eloquent and as focused as you are (although I fully admit I may have been too stupid to enjoy wrapping my brain around their philosophy and formalism).

While none of what you write about is new to me, I walk away from reading your work with an enhanced clarity of thought — thank you very much!

I always felt thunderstorms would cool an “overheated” earth. However I also imagined that was why a “hot spot” had to be created high up in the troposphere in the tropics, in order for the models to alarm. Such hot air aloft would prevent the formation of thunderstorms, and keep thunderstorms from cooling the tropics. As soon as reality failed to show any tropical “hot spot,” Alarmism sprang a major leak and started sinking.

Thunderstorms are like a safety valve. When they fail to occur, (as in the case of the major “heat high” that caused the Dust Bowl,) you get your most murderous heat and worst drought.

at one point you say “The dry surrounding air is drawn in, loaded to the brim with moisture via the increased evaporation, and shot skyward at rates up to 10 m/sec”

Moist air will not generally travel upward at 10m/sec, probably about half that. (gravity/specific heat) However, approximately the same amount of energy is moved upwards.

I’m no glider pilot, so I don’t have a good understanding of life under a thunderstorm (which is the context of the 10 m/sec).

Once in a thunderstorm, updrafts can be much greater than that, witness hail formation. In 1960 Lt Col William Rankin became one of the first people to ride a parachute through a thunderstorm did it the hard way – by ejecting from a powerless F8U at 47,000 feet, above a thunderstorm. While there aren’t estimates of wind speed in the storm, he spent at least 25 minutes in the air and endured accelerations that must have led to velocity changes at least 10 m/sec.

A very well written article but overlaps with a lot of points that I and others have been saying for some time, notably:

i) That his thunderstorm hypothesis is sound but needs to be extended to the entire globe which is what he has now started to do..

ii) That as per my suggestion from some time ago ENSO occurs because the ITCZ is on average north of the equator which introduces an imbalance in solar input to the oceans either side of the equator. That imbalance builds up over time and periodically discharges into the northern oceans in El Nino pulses of warm water.

iii) He says this:

“The boiling water system simply moves energy through it at a faster rate, it doesn’t run any hotter”

Which is the analogy I have used several times in the past and have linked the boiling point of water to surface pressure which leads naturally on to the ideas of me and tallbloke concerning the effect of surface pressure on ocean temperatues and energy content.

In the past Willis has been very abrasive about so called ‘pressure heads’ but here he is close to conceding the point.

iv) “So increasing input may only increase the throughput, rather than increasing the temperature”

Exactly as I have been proposing but the faster throughput does involve a global circulation change as in the speed of my adiabatic loop.

v) “So when the forcing from CO2 increases a watt or two, in an accurate model the clouds will emerge a few minutes earlier on average across the tropics, and the balance will be restored. This system of control by emergent phenomena has worked very well for billions of years, and it handles large swings in radiation every single day—it won’t be altered by a few watts of extra forcing from CO2″

Been telling everyone that for 6 years but referring to the entire global circulation rather than just the diurnal timing of regional events.

Great work as usual…
Living here in Panama, right under the ITCZ for much of the year, my reaction to first reading your thermostat theory was, well of course that is how it works. How else could you explain that the temperature where we live is virtually constant morning, noon and night all year. Thanks for fleshing out the story.
Here is a bit of a testimonial: We live at 1200 meters (4200 ft.) about 40km from both the Pacific and Caribbean coasts. During the rainy season, we sit right under the ITCZ and watch the thunderstorms rolling up the mountain from the Pacific. Here are the rainy season average temps for last year:
May 67.5
June 67.6
July 69
Aug 67.2
Sep 67.6
Oct 66.2
Nov 67.6
Dec 67.3
The min and max temps also fall consistently between about 58F and 81F. Glancing a the data,http://www.boqueteweather.com/climate/data_annual.htm
If that isn’t the action of a thermostat, I don’t know what else to call it. Rainfall varies wildly (24″ in May, 1″ in Dec), but temps never vary. Our house has neither heating nor air conditioning and not once in five years have I put on a long sleeved shirt in the house or felt uncomfortably hot.
Keep at it Willis – it took Alfred Wegener a very long time and a lot of derision before his ideas about continental drift were accepted – and today, we look at the Earth and say, “Duh, well of course that’s how it works.”

Dredge up links and references and shop this to computer modelling journals.

There are directly testable hypothesis stated here. For starters, carpet-bombing a single tropical oceanic gridcell with extensive temperature/pressure/wind/sunlight/humidity monitoring would be interesting.

The term “Climate Sensitivity” I’d mostly replace with something that highlights the local-and-instantaneous nature that you’re referring to though.

Excellent and very compelling article. I hesitate to mention a couple of points which still puzzle me: During the Wet season (with high humidity and upper and lower atmosphere instability) clouds pop up and begin mushrooming very soon after dawn, and thunderstorms can occur at any time of the day or night. Perhaps time of day is not so important as energy available and conditions encouraging stronger convection? The energy in the atmosphere presumably is being stored in the humidity and only a little (relatively) extra energy (from the sun or from convergence from a local or regional upper level low pressure) will generate thunderstorms. However the high humidity and the resulting cloud development generally keeps the surface temperature much lower and fairly stable over many days. Can your idea be generalised to cover time spans longer than daily e.g. many days for the life of a tropical cyclone, or the active phase of the monsoon?
And re a previous comment doubting that humid air can rise at 10m per second- too right it can, and much more too. Don’t deliberately fly into a thunderstorm.

I do enjoy reading your work. Keep going – IMHO you are right on track.

So if there is a bit of additional forcing and the surface is a bit warm, the clouds simply form earlier, and the thunderstorms form earlier, and the nightly overturning of the ocean starts earlier … and that balances out the additional forcing, just like it has done for millions of years.

And that is why our modelled future is just that. Add some more CO2 – the whole tropical ‘theatre’ moves back ten minutes. Up the output of The Sun (within reason) – the whole tropical ‘theatre’ moves back ten minutes. More telling … decrease the output of The Sun and the whole tropical ‘theatre’ might not happen at all. All those thunderstorms might just turn into a huge equatorial blanket of fog.

What actually happens is sort of vaguely analogous to a heavy truck going up hill.

It slows down all the other traffic , then once released at the top of the hill, takes off like a bat out of hell, and all the following cars go with it.
So yes, you can get updrafts that are a lot faster, but on average, the same energy is transferred (minus latent heat), so the average updraft must be slower.
Below thunderstorms, it can be one chaotic mess, plus of course there is upward suction from condensation pressure differentials, so again, updrafts can be much faster.

So does this mean that serious divergence, such as the little ice age and the long term glaciated ice ages may be caused by unknown emergence’s? Also if the feed back correction is possibly that good, how can “some warming” be ascribed to the increase in CO2 with any assurance? Other possible factors with land based temperature measurements are the potential changes in local conditions even at a well sited locations. For example, changes in local vegetation or ground cover, especially with the increase in CO2 (plant food) may affect the local site environment thermal characteristics. And as someone else has previously pointed out, even a short distance away the thermal/temperature differences may be major depending on the terrain. Sea surface measurements should be better, but are they when considering potential pollution sources such as trash dumping and liquid contaminant pollution from land runoff and oil leaks?

“there is no relationship between incoming energy and temperature”
So when the sun sets what happens?
No relationship?
or a complex relationship.
or a relationship we dont fully understand?
or a relationship that is fundamentally not quantifiable?
lots of ways to interprete that sentence.

The claim of no relationship is pretty hard to maintain. In fact its pretty hard to prove the non existence of a relationship. But lets compare it to something where we are pretty certainthere is no relationship: there is no relationship between the weight of an object and its color. I’m holding something that weighs a pound: Does that give you any information about its color? nope. no relationship.

Tell me the energy into the system goes from 1360 watts to zero watts and I do know something about the temperature. it’s why I wear a coat to the football game at candlestick.

Yes, and life, the ultimate (so far) emergent property will never be reduced to chemistry or physics. Indeed, physics has foundered on quantum mechanics and the indication that we create reality by merely observing it. Now they are off willy nilly on paralell universes and angels dancing on the head of a pin. But it is worth bearing in mind that even the earliest climate models were able to get register for emergent phenomena including el nino. The register had no predictive value, however. It was like poetry and the notions like the atom as a microcosm of the universe or ontogeny repeating phylogeny. There is poetic truth but no predictive value. Perhaps the nature of emergent phenomena.

Some would credit my lack of organization on Autism, or just laziness, but I seem to recall that to get a 5” hailstone requires a 160 mph updraft. Back of the envelope, that comes out to about 234 feet per second. How much energy is that per square meter in the rising air? Ten meters per second doesn’t sound unreasonable here.
Off on another tangent, I seem to recall a study of hailstones in Louisiana that display an inordinate amount of them that have at their very center a bacterium (or was it some other carbon based microbe?) that is structured perfectly with attractors to form the nucleus of an ice crystal.
Once again I apologize for a lack of links, but the more astute among you will find out (or not).
I just wonder how many of these emergent phenomena are out there?
All that aside, Willis Eschenbach, thank you, thank you, thank you,
john

Mosher,
“So when the sun sets what happens?
No relationship?
or a complex relationship.
or a relationship we dont fully understand?
or a relationship that is fundamentally not quantifiable?
lots of ways to interprete that sentence.”
I’m hoping that you haven’t really read much of this essay, if not, it speaks volumes about you.

Edits: “homeostatic mechanism are located” — is, or –s are
“I’ve shown that at the TAO buoys, days that start out colder than average end up warmer than average, and days that start out colder end up warmer … ” Same. Should be complementary.

Yep… A number of scientists are enamored with trying to measure feedbacks and applying months long lag times and smearing data to see ancient responses in phenomena that are long gone. They are just seeing faint reminders of what caused the changes they want to measure in the first place. They are missing the point entirely as you have pointed out.

You need to be measuring instantaneous responses on much smaller scales to capture anything important to the system. I’ve wanted to do just that, by taking more of a pixel by pixel analysis of minute by minute changes on satellite images. It should be possible to get water vapor, visible light, and IR all on the same tiny grid or map, even if not from the same satellite. Then you watch for the changes and describe how the changes progress, and what changes influence other changes, during events. The emerging storm changes in visible and IR would go a long way in describing various phenomena, not just in the tropics, but anywhere. Then you could do clear nights, hazy, cirrus, whatever. I think we have enough resolution to capture a lot of what you want. And you would need it in very small pixels to see the speed and true magnitude of the various factors. I think people would be blown away by how powerful the regulating effects you describe really are. And it would most certainly further wreck the already demolished models, if that is even possible. And you’re right about CO2 in the tropics. I don’t think you could budge the temperature no matter how big your hammer was.

Once all of the small scale phenomena have been reasonably well described, you would have at least some hope of simulating their effects even using larger grid scales, even if you can’t make the phenomena themselves. I’m baffled why this hasn’t been done yet, it seems like I’d be able to write all of that in a few weeks if I wasn’t working 12 hour days at a real job. It doesn’t sound difficult at all, it sounds like a blast.

I’ve agreed with you for years, I’ve just never heard it put quite like that… Great stuff. Thanks.

Spot on as always, Willis.
The fact that climate scientists are willing to put so much faith in averages is a puzzle to me. Anyone who has experienced weather – i.e. those of us who are not closeted in cubicles queueing up at the supercomputer for the next run of our model – know that averages conceal more than they reveal. In the temperate zones where most of us live, only rarely do we experience “average” weather. We might get a fair amount of “typical” weather for the time of year, but we routinely experience days that are several degrees warmer or colder, or wetter or drier, or clearer or cloudier, than the so-called average.
I do not think it is reasonable to summarise a month’s weather for a station in a single number that represents daily Tmax+Tmin/2 averaged over 31 days, even if temperature were a good proxy for a chaotically dynamic system like weather. As it is a rubbish proxy for a system that is all about enthalpy, i.e. total sensible heat plus latent heat plus kinetic and potential energy, it is risible to confidently predict catastrophe on this basis, especially when the trends are all over the place for different locations. Not to mention the flaws in the measurement processes and data-diddling that goes on.
The only places that experience “their own weather” to a significant degree are the tropics and the poles. Everywhere else mainly gets weather that has come from elsewhere, which may be hotter or colder according to the wind direction. The tropics are clearly the great heat engine of the earth, in which multiphasic water is the key moderator, and from whence much of the heat that affects the mid- and upper-latitudes comes.
From casual observation (I intend to do some more detailed work on this) the majority of cities in the tropics experience daily max temperatures of about 32-33C. This is also the typical maximum temperature of the sea, as Willis’ recent article on the TAO buoys showed. Coincidence? Or is this another indication that everything is about water? It’s certainly got bugger-all to do with our favourite plant food, which can only look on with envy as water does the heavy lifting.

BFL says:
February 7, 2013 at 6:52 pm
So does this mean that serious divergence, such as the little ice age and the long term glaciated ice ages may be caused by unknown emergence’s?

A very good question.

Whenever this subject comes up, I always think of the Younger Dryas. In somewhere between 10 and perhaps 50 years the Earth cools between 5C and 8C. It stays there for 1400 years and then warms 5C to 8C in somewhere between 10 and 50 years.

IMO none of the proposed causes of the YD explains both the start and the end and the stability in between.

Willis talks about the role of the phase changes of water in thunderstorm emergence, and I think that’s where the answer lies to the YD. Increased Galactic Cosmic Rays seed clouds sooner and the thunderstorm thermostat gets set 5C cooler.

Glacial cycles are largely driven by Milankovic Cycles, but emergencies, known and perhaps unknown, likely play an important role.

Willis, this is a great essay and a complete contrast to that unfortunate “Steel Greenhouse” thread. Here you have considered many of the things missing from “basic physics” of the failed AGW hypothesis. You consider the transport of energy by the physical movement of gases, the transport of energy above the level of maximum IR opacity before the release of latent heat and increased surface cooling by atmospheric circulation.

>>>>>“An example of this is the spontaneous emergence of “Rayleigh-Bénard” natural circulation in a fluid heated from the bottom and cooled from the top.” Image

That image is a great find. It brings up two important points. First the average near surface temperature before breakaway at the 4 second mark is hotter than any of the images where circulation is developed. The second is the fact that the circulation only develops with cooling higher up. Radiative gases are the only means for achieving energy loss at altitude in our atmosphere.

>>>>>“…thunderstorms begin to form. These cool the surface in a host of ways, most importantly by piping the warm surface air through the middle of the thunderstorm up to high altitudes. This avoids almost all of the greenhouse gases (H2O and CO2) in the lower troposphere, and allows for free radiation of huge amounts of thermal energy to space. Not only that, but thunderstorms are radically different from a feedback, because they cool the surface down to well below the thunderstorm initiation threshold temperature. This means that they can not only slow down a temperature increase, they can stop it in its track.”

>>>>>“The temperature of the boiling water can no longer be even approximated by looking at how much energy is going into the water. The boiling water system simply moves energy through it at a faster rate, it doesn’t run any hotter”

Here you are so close to the answers –
– if convective circulation stalls our atmosphere will heat
– radiative gases are critical for continued vertical convective circulation in the troposphere
– The NET effect of radiative gases is cooling at all concentrations above 0.0ppm
– adding radiative gases to the atmosphere will not reduce its radiative cooling ability

But there is still this little problem…
>>>>>“During the nighttime, the surface is still receiving energy from the GHGs. This has the effect of delaying the onset of oceanic overturning, and of reducing the rate of cooling.”
Willis I have checked this empirically and it does not work. Incident IR does slow the cooling rate of solid materials and I have found the effect easily measurable. However there is no measurable effect on liquid water that is free to evaporatively cool. I know the AGW calculations say that the oceans would freeze without DWIR, but those calculations are total tripe. I strongly urge you to design and build your own empirical experiment to check this.

“During the nighttime, the surface is still receiving energy from the GHGs”
==================
Where are the GHG’s getting the energy at night? They aren’t capacitors. They recieve 80% of their energy from the surface and the other 20% from the sun. When the sun goes down the candle goes out for GHG’s as well.

This looks like it could turn out to be an important peace of work in the understanding of climate and weather, but it’s not clear how much it would minimize the role of GHG’s in the current warming trend. You’ve shown this thermostat effect over tropical oceans. The GHG’s are always operating over the whole globe, even at night, if I understand correctly.

This all seems to depend upon the nature of water. It changes state at a certain temperature. We can understand why the earth does not heat up — but are there any emergent phenomena that prevent global cooling? I mean at one time the earth was an ice ball. Due to the properties of water run away global warming may be impossible — we have never seen it in Earth’s long history — but we have seen what could be described as run away global cooling.

Or have we? Funny but the lack of such emergent phenomena allows warming of the earth. So could we say that the earth naturally warms till emergent phenomena appear to cool it? All due to the properties of water?

So does it all come down to how “hot” the sun is (or about the earth’s changing orbit reducing the amount of energy we receive from the sun)?

And strangly we can ask the question is ice an emergent phenomena? Water is weird. As a solid it is less dense than as a liquid. Does that have a mitiagating effect on lower solar energy? The earth itself generates heat. Does ice trap that heat causing the interior of the earth to warm? So does what ends ice ages come from below the ice?

Wow, so counterintuitive. The creation of an ice cover facilitates global warming.

Eugene WR Gallun

i am absolutely sure that other people have specualted about what an ice cover does. This is just a fun steal on my part.

As always Willis, you impress with your broad knowledge and ability to explain things very clearly. Despite its length, this was a pleasure and easy to read.

This also accounts for something I have been suggesting for about a year now, that there is no net cooling from major stratospheric volcanoes. They block some of the incoming solar energy but you explain how this will be compensated by later on set of thunderstorms.

For a small change, like AGW, this can probably be adjusted directly on a daily basis. For major disruption like stratospheric eruptions, it may take longer. Like the drunk, there are limits to the magnitude of the thunderstorm mechanism. Any such positive feedback mechanism is highly unstable and must be bounded by an even stronger negative feedback. (Once there is a clear sky there can be more warming feedback. Once the region is full of cloud there can be no more cooling feedback. There are rails of the drunk on the walkway.)

For this reason it may take a few years to recover the lost heat input caused by a VE5 or VE6 but I think you have provided a direct explanation of how this happens.

There are published studies showing that La Nina events are more likely after major volcanoes and the El Nino / La Nina thresholds of 0.5C are specifically chosen relative to the thresholds you refer to in the onset of deep convection thunderstorms.

The corollary of volcanoes being climate neutral (beyond the scale of 5 or 6 years) is that the ‘parametrised’ PERMANENT cooling effect that is built into the models is unwarranted and incorrect. It is this supposed cooling effect that requires an enhanced sensitivity to CO2 , which is achieved by adjusting ‘parametrised’ cloud cover in the tropics.

Without the supposedly permanent temperature drop cause caused by volcanoes, no more justification for exaggerating the known physical ‘forcing’ effect of CO2.

WATER regulates climate on Earth, not CO2. Until the models can model evaporation, cloud formation and precipitation (especially in the tropics) they are of no use to anyone.

That’s not to say they never will be an we should stop trying but until they reach that point it is dishonest to pretend they have any value for predicting or understanding climate.

Willis: Parameterization of complex phenomena also occurs in physics simulaitons, when they are beyond the reach of the simulation computers, or the known physics, or the minds of the researchers. Your attack would be considered naive by many people working of complex engineering problems because the job must get done. I have personally witnessed many researchers getting ahead using bad code that imitated the behavior du jour but which lacked rigor. In other words, parameterization vs simulation of emergent or even complex behavior is a much more widespread problem whose main cause it the desire to advance one’s career.

On another blog a few weeks ago, discussing the Met Office’s certainty about climate change, I opened my comments by saying “climate is complex”. A reply to my comment stated the following:

“Anyone who pretends that climate is complex clearly has no idea what they’re talking about. The climate of anywhere on earth is mainly determined by the temperature, humidity, atmospheric pressure, wind, precipitation, and atmospheric particle count; all of which are easy to measure.”

Thanks, Willis. This nicely summarizes my non-expert opinion why CAGW is crap: (1) We are here, and (2) crap-sellers always make the error of selling you too much, e.g. that some science is settled. For the young ladies: if a lover gives you expensive jewellery within the first hour, look around for someone else.

Your post at February 7, 2013 at 6:52 pm is a mish-mash of misunderstanding and irrelevance. In total it says

So does this mean that serious divergence, such as the little ice age and the long term glaciated ice ages may be caused by unknown emergence’s? Also if the feed back correction is possibly that good, how can “some warming” be ascribed to the increase in CO2 with any assurance? Other possible factors with land based temperature measurements are the potential changes in local conditions even at a well sited locations. For example, changes in local vegetation or ground cover, especially with the increase in CO2 (plant food) may affect the local site environment thermal characteristics. And as someone else has previously pointed out, even a short distance away the thermal/temperature differences may be major depending on the terrain. Sea surface measurements should be better, but are they when considering potential pollution sources such as trash dumping and liquid contaminant pollution from land runoff and oil leaks?

It seems that you have failed to understand any of the above article.

The Little Ice Age (LIA) was not a “serious divergence” it was a slight variation in global temperature of less than 1%.

Interglacials are shorter “divergences” from “the long term glaciated ice ages” which are the normal state of the Earth. Emergent properties – be they known or unknown – may or may not be the cause of transitions between these states.

You ask,
“Also if the feed back correction is possibly that good, how can “some warming” be ascribed to the increase in CO2 with any assurance?”
The question is surreal because there can only be a feedback response to something (e.g. “some warming”) which exists.

And you also ask,
“Other possible factors with land based temperature measurements are the potential changes in local conditions even at a well sited locations. …. Sea surface measurements should be better, but are they when considering potential pollution sources such as trash dumping and liquid contaminant pollution from land runoff and oil leaks?”
This question is a complete ‘red-herring’. The article is not about accuracy, reliability and/or precision of temperature measurements.

In summation, you need to read the article again with a view to understanding it. The effort would be worth your while because the article is very good and you may learn something.

Your post at February 7, 2013 at 7:53 pm is mostly snark so could be thought to be not worthy of an answer. But it may mislead onlookers so I write to address it.

Willis article is about heat removal from – and distribution within – the Earth’s climate system. Your failure to understand any of it is demonstrated by all of your post. And your misunderstanding of the article is explained by an assertion at the end of your post. It says

Tell me the energy into the system goes from 1360 watts to zero watts and I do know something about the temperature. it’s why I wear a coat to the football game at candlestick.

When told the energy into the system you know nothing about the temperature unless you also know the energy out of the system. The rate of energy out of the system is why you wear a coat to the football game at candlestick.

Very important to bring us back to the essential fact of the nonlinear / nonequilibrium emergent character of climate.

The only earth in which nonlinear / emergent dynamics would NOT dominate climate is an earth with climate equilibrium, in which the oceans were stagnant ponds (no current) and the atmosphere a permanent static doldrum (no wind). In such a world, current GCM climate models MIGHT make some sense.

Nice to see some literature analogies posted in response to this thought-provoking article:

Richard G says:
February 7, 2013 at 10:01 pm“There is nothing- absolutely nothing-
half so much worth doing
as simply messing about in boats.”-Ratty said to Mole

Gary Hladik says:
February 7, 2013 at 2:50 pmFrodo: “You’re late.”
Gandalf: “A wizard is never late, Frodo Baggins. Nor is he early. He arrives precisely when he means to.”
— “The Fellowship of the Ring”

phlogiston says:
February 7, 2013 at 1:15 pm“Human being says: “It never rains but it pours.” This is not very apt, for it frequently does rain without pouring. The rabbits proverb is better expressed. They say, “One cloud feels lonely”: and indeed it is true that the appearance of a single cloud often means that the sky will soon be overcast. However that may be, the very next day provided a dramatic second opportunity to put Hazel’s idea into practice”

Watership Down, Richard Adams

In the Watership Down quote the proverb “one cloud feels lonely” is referring to the Lyapunov stability of clouds (they quickly multiply and persist longer than they should) which is well understood by all rabbits.

I see emergent behaviour every day in the most mundane of materials — clay soil. Fine clay turns into a nightmarish sticky bog when wet, but a week’s strong sun later, and working it is like trying to eke an existence planting in the Negev Desert.

Now, one idea to stabilise the clay is to embed stones in it during the wet times. It doesn’t work — the clay just spits these intruders back out. How? When clay dries, it compresses, and the deeper you go, the more it compresses, because of the weight of the clay on top.

So any object inside the clay feels an overall slight upward force, due to the variation of compression, and soon the stones come merrily back to the surface.

BFL says:
February 7, 2013 at 6:52 pm
So does this mean that serious divergence, such as the little ice age and the long term glaciated ice ages may be caused by unknown emergence’s?

A very good question.

Whenever this subject comes up, I always think of the Younger Dryas. In somewhere between 10 and perhaps 50 years the Earth cools between 5C and 8C. It stays there for 1400 years and then warms 5C to 8C in somewhere between 10 and 50 years.
===========

The general pattern of glacial / inter-glacial periods is indicative of a similar kind of process to Willis’ thunderstorms and the drunk on the path. That is a positive feedback , bounded by a stronger negative feedback.

The positive feedback causes the system to latch into one or other state and to pass rapidly from one to the other. The negative feedback ensures that the system is bound to remain within stable limits , limiting the range of the positive feedback swings.

It is possible that CO2 provided such a positive feedback at the end of the last glacial. Emerging plant life may have eaten enough of the new “excess” to cause a brief flip back, or whatever was ending the glacial may have eased or stopped and the positive feedback caused run-away cooling.

That is hysteresis. As someone else commented this is different to overshoot.

Slight overshoot may describe the post-YD ‘peak’ of several 1000 y before the last 9000y or so of cooling.

> The positive feedback causes the system to latch into one or other state and to pass rapidly from one to the other. The negative feedback ensures that the system is bound to remain within stable limits , limiting the range of the positive feedback swings.

Negative feedback is not the only way to remain within stable limits, and in the case of climate extremes like glaciations, it does not seem to have a role in establishing these limits. It may have a role in limiting the duration of one state or another, but that’s a different story.

In control systems, the stable extremes are either determined by structural limitations (control arm hitting a bumper), or by a limited power supply. It is actually not easy to come up with a negative feedback that would stabilise both extremes.

“My thesis is that systems with emergent phenomena cannot be analyzed in the same manner as systems without emergent phenomena. ”

Wolfram shows in “A New Kind of Science” that of 256 possible cellular automata of a certain class (one-dimensional cellular automata, with a rule table that allows exactly 256 different combinations), there is a subclass that develops unlimited and unpredictable complexity (while MOST of the possible rules result in trivial or cyclical behaviour).

Where “unpredictable” means – not predictable without perfect simulation of the system – you have to RUN the automaton to see what it’s doing, in other words. (Principle of computational irreducibility)

All natural systems are WAY more complex than Wolfram’s class of automata yet even in that super-simplified example emergent phenomena occur.

Very interesting article. As someone who has lived in the tropics – unlike most of the CAGW advocates I suspect – the behavior of thunderstorms as a cooling off mechanism is something I have personally experienced.

A few notes on your hypothesis:

1) Your working model on the 3 states of energy behavior are interesting because they would explain why we are seeing ‘higher lows’ rather than across the board temperature increases. It isn’t that the highs are increasing, it is that the lows of the day are, and thus the ‘average’ increases. The mechanism thus is that the CAGW folks are right in the sense that more CO2 equals more GHG heat, but that they’re wrong in saying that all this heat has nowhere to go. Under your hypothesis, the increase in heat only matters in the transition into nighttime – during the day said extra heat is simply vented by existing homeostasis mechanisms.

2) Having said the above, there seem to be some implicit assumptions. I believe you are assuming that clouds don’t form at night? Is this a generally accepted fact? More importantly, as the nighttime temperatures rise, is there any possibility of this changing? Related to this is that you are also assuming thunderstorms only happen in the daytime. I don’t think this is true, though I do believe thunderstorms happen mostly in the daytime.
Another issue is the thunderstorm as the primary heat transfer vehicle. Thunderstorms are common in high energy and/or high differential areas, but I think to be credible, you’d have to also find some type of mechanism for the other areas – both temperate and cold regions.

Willis says:
Now, note that I didn’t say that this kind of system containing emergent temperature control systems was impossible to model … just that it is hard. … It could be done. But it can’t be done the way that they are doing it, because their way doesn’t account for the emergent phenomena.
————————————————————
I’ve wondered about this, whether or not it’s possible in theory to model climate handling Willis’s emergent phenomena. By ‘possible in theory’ I mean computationally feasible. For example, while it’s possible in principle to minimax map chess and use the results to play THE perfect game, it involves evaluating exponential possibilities and is computationally infeasible (back when I was in school my professors called problems like these non-deterministic polynomial meaning that while no way is known to solve the problem in ‘polynomial time’ on the inputs, you could at least write an algorithm to check the answer supplied by some unknown / non-deterministic technique in polynomial time). The point is, if something takes exponential time to work out – if you’re forced to build the whole tree of possibilities by walking down every possible branch, it’s generally only feasible for very small problems. Note that it isn’t really a function of the speed of the computer but of the work the algorithm needs to do.

Philip Bradley says:
February 7, 2013 at 2:00 pm
My experience of Singapore and the Riau islands (within 100km of the equator) is that it rains at all hours of the day and night and there is no noticeable late afternoon rainfall peak. I tried to find a reference but couldn’t. Presumably no one has studied this. I’ll suggest the regime you describe occurs where humidity levels are somewhat lower than the high humidity levels close to the equator.
======
I’ve seen the same on the equator. The sky is fully clouded for days on end and rain is continuous. It can lasts for a couple of weeks at a time. Usually there is little wind and the rain never lets up. Typically during the hottest part of the year. My theory was that it was like a massive, stationary tropical storm that never started rotating.

c1ue says:
February 8, 2013 at 6:43 am
2) Having said the above, there seem to be some implicit assumptions. I believe you are assuming that clouds don’t form at night? Is this a generally accepted fact?
==========
This is generally true in the tropics. Clouds form in the afternoon, more commonly during the wet season, then by morning the skies are clear.

There is also a vertical movement in the clouds. During the day the mountain tops are clouded, but at night they clear as the clouds descent and the sky overhead is crystal clear. The classic example is the Mona Loa observatory in Hawaii. Cloudy during the day, clear at night.

The idea of an emergent is why climate science has moved from the newest fad phenomenon, used to explain almost everything, to the next new phenomenon. I remember when El Nino first “hit the news” because it moved north to impact California in 1982-83.

Hitting California made it newsworthy, but from an emergent perspective it was the change in pattern that was the actual catalyst. The authors of the article cited talk about it being “anomalous” but that definition is only a function of the length of the record and the pattern of emergents.

El Nino began as the Walker circulation and there was no mention of La Nina for some years. Other oscillations, such as the PDO, QBO or NAO, appeared over the years as they emerged in the record for the first tme or reach different peaks or patterns. This also underlines the claims about interacting cycles as the predominant way in which the net effect, we call weather, is created. It illustrates why the 30 – year normal of the World Meteorological Organization (WMO) is so meaningless and misleading. It is why William Briggs’ abhorrence of smoothing long term series is such a valid dictum.

The idea of emergents also speaks to the problem of leaving out variables because their input is considered marginal. The variable may be marginal under one set of conditions, but as those conditions change the variable becomes increasingly important. I remember concern in agriculture when addition of more fertilizer was not increasing yields, in fact, yields were declining. They eventually discovered that the trace minerals, particularly zinc, excluded form their calculations was necessary of the plants ability to uptake some of the other fertilizers.

Another problem identified by the concept of an emergent is the severe limitation on computer models. They must leave out variables because of inadequate capacity or lack of data, but they also guess how the variable interacts with other variables that likely does not reflect reality.

What are we to make, from an emergent perspective, of IPCC (Ch.8 2007) acknowledgment of limitations such as

“Unfortunately, the total surface heat and water fluxes (see Supplementary Material, Figure S8.14) are not well observed.”

or

“These errors in oceanic heat uptake will also have a large impact on the reliability of the sea level rise projections.”

or my favourite

“Due to the computational cost associated with the requirement of a well-resolved stratosphere, the models employed for the current assessment do not generally include the QBO.”

Not only is the science not settled, but chances of reaching even minimal understanding is limited by the data and records available. Speaking as Sherlock Holmes, Sir Arthur Conan Doyle wrote, “I have no data yet. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”

Probably the best exposition of how emergent phenomena emerge, and how to understand them, and what they do, is contained in Hofstadter’s book ‘Godel, Escher and Bach – an Eternal Golden Braid’. Amongst other things, it is an exposition of Hofstadter ‘s concept of intelligence, and the mind, as an emergent phenomenon.

This actually answers a question that has puzzled me somewhat all these years. Back when I was in the Navy and assigned to Guam, rainstorms would come every day between 2:00 pm and 4:00 pm. I always wondered why, since the island is in the middle of nowhere. Although it rises up to 700 ft above sea level, that didn’t seem to me to be enough to get the consistent rain that we did.

But looking back, I can see that clouds started forming late morning and became thunderheads by early afternoon.

Clouds didn’t form anywhere with the same regularity during other parts of the year.

I spent a few years in the Sahel of northern Nigeria in the mid 1960s mapping geology, lecturing at the Nigerian School of Mines in Jos, (which I assisted a Polish metallurgist, Jan Fiegel, rest his beautiful soul, to set up), evaluating groundwater resources for town water supply, assisting indigenous miners to open up deposits and build processing facilities, identifying minerals, etc. When the wet season came to this dry land, it was in the form of massive thunderstorms with torrential rain – all starting about 3 to 4 in the afternoon. If you were 100 feet from your door and the first drop of rain hit you, you would be drenched right through before you got inside. Often, it was accompanied by such a fall of hail that it would look temporarily like Saskatchewan in January out the window. The hail, by the way was called kunkalie in Hausa – it was gathered and buried in the ground with straw and earth and used as a “medicine” for such things as scorpion bites, etc. After such a storm, it was indeed very cool for an hour or so.

“These cool the surface in a host of ways, most importantly by piping the warm surface air through the middle of the thunderstorm up to high altitudes. This avoids almost all of the greenhouse gases (H2O and CO2) in the lower troposphere, and allows for free radiation of huge amounts of thermal energy to space. ”

does not compute.
the warm surface air “piped” does not avoid H20 or C02.

[..] “there is no relationship between incoming energy and temperature”
So when the sun sets what happens?
No relationship?
or a complex relationship.
or a relationship we dont fully understand?
or a relationship that is fundamentally not quantifiable?
lots of ways to interprete that sentence.

Yet again Mr Mosher you attack with all the finesse of a “cult of doom” zealot. Let’s re-examine the paragraph from which you lifted your attack (“there is no relationship between incoming energy and temperature”).

Here it is, in full. (bolding mine)

But in the thunderstorm part of the tropical thermal regime, it is important to note that not only is the relationship between incoming energy and temperature non-linear, but in fact there is no relationship between incoming energy and temperature. So you cannot even approximate it with a linear relationship. In that regime, increases in incoming energy are generally balanced out by increases in thunderstorm numbers and associated increased evaporation and convection, leaving only small residual temperature changes.

Erm … your response looks a bit different now doesn’t it? Get a grip Mr Mosher. I don’t mind you attacking a post or the comments, Leif Svalgaard does it all the time but at least he has the decency to quote with context and provide ‘evidence’ for his POV. Something to think about perhaps?

Willis – I read your post last night and, after reading a lot of the comments today, I had to read it again. You have my every sympathy. It would be nice if some folk actually read your post before commenting.

Willis,
Wonderful essay.
I’m wondering whether your choice of Drawing Hands by Escher imples your thoughts on emergent phenomena have wandered through the book Godel, Escher Bach: an Eternal Golden Braid by Douglas Hofstadter. Or has that picture inspired you and DH independently?

Well written and succinct. Despite that, I remain confused on a few points. The article seems to me to be saying that for a very broad set of initial conditions, those emergent phenomena act as negative feedback mechanisms, keeping the temperatures near a chaotic attractor point. I understand your analogy about the guard rails but the consequences that you describe when the environment shifts from one regime to another is a move back toward the conditions where the first regime controls. A thunderstorm is a fundamentally different atmospheric model and can cool the surface below the initial temperature that created it but the intermediate-term consequence you describe is a cooler surface the next morning (or next week) and a later start to the next daily cycle.

How does that mental model reconcile with the geological and historical records which DO show variations in temperature? Oceans and thunderstorms still existed in those eras. Why were they unable to mediate the Little Ice Age or the Medieval Warming Period?

Or is your point just that the climate models can’t be trusted until they CAN explain the LIA and MWP (and that you think they will need to incorporate emergent phenomena before they can)?

Very nice simplification, Willis, and a nice thought experiment backing
up your thesis that “Thunderstorms/hurricanes” act as the Earth’s
thermostat.

I wonder–is the neglect of this phenomenon why, for instance, Hansenet al.‘s GISS modelE, described in the journal Climate Dynamics
in 2007, shows climate forcings off the West coast of continents to be
~50 W/m^2 too high?

ferd berple says:
February 8, 2013 at 7:50 am
c1ue says:
February 8, 2013 at 6:43 am
2) Having said the above, there seem to be some implicit assumptions. I believe you are assuming that clouds don’t form at night? Is this a generally accepted fact?
___
Cloud formation is a function of the temperature – dew point spread. When these converge clouds emerge. When they diverge clouds dissipate.

“up to 10 m/sec” I’m a paraglider and hang glider pilot. I’ve been in thermals faster than that, with only small cumulus clouds above, in sunny days, in spring or summer, in temperate area. No need for a storm to have that. Regular convection is enough. Storms can be very, very bad for a paraglider/hang glider pilot. The updraft can be so fast that you have no chance, but die. Look it up, a woman reached almost 10000 m (and survived!). Recorded 20 m/s. She was lucky. It can be much higher. In a severe thunderstorm, in a ‘freefall’, you might be climbing!

Me says: “I’ve been in thermals faster than that, with only small cumulus clouds above, in sunny days, in spring or summer, in temperate area.”

I thought about making a similar comment earlier, but it wasn’t a first-hand experience, so I held it back. I heard an account from a friend who was dragged above the clouds during a plain-vanilla parachute jump somewhere in Canada. That was in the days before paragliding took on and people were not properly trained to steer their parachutes. He said he was in a panic because his attempts to exit the updraft slowed the climb only insignificantly while making him spiral at a sickening rate. I forget the altitude he reached or the time it took, but he claimed both were extraordinary.

Good essay. I would add that, since “phenomena” are the human (mental) responses to the events in the physical world, the “emergence” is an emergence in perception or consciousness or theory. More complex than the Gestalt figure/ground reversals and such (the human concept of species, for example where nature provides lineages, or perceptibly different colors, musical tones, and phonemes), but a psychological discontinuity in what is a natural continuum. El Nino and La Nina are “emergent” from the natural oscillation in that they appear conceptually to be “more than” what is expected (another psychological term) from studying the rest of the natural oscillation. In dynamical systems theory, such seemingly abrupt changes are represented by “catastrophes” (large perceived responses to small changes in inputs) and “bifurcations” (large perceived changes in behavior of the system caused by small changes in parameters. (“Large” here is in a psychological sense, such as “period doubling”.)

I wrote “good”: it’s at least as good as the average paper in “Scientific American” (as I remember from youth, I have not seen recent issues) or “American Scientist”.

Tim Ball: The idea of emergents also speaks to the problem of leaving out variables because their input is considered marginal. The variable may be marginal under one set of conditions, but as those conditions change the variable becomes increasingly important.

Indeed. “Emergents” result from the disciplined use of “Occam’s razor” to avoid complications in explanations until those complications become absolutely necessary. The evaluation of when “necessity” has “emerged” in the data and phenomena is a human judgment, not an “absolute” of Nature. This is why I am always harping on the “equilibrium” assumption in the climate debate: I think that the standard CO2 theory is too dependent on that assumption, it’s too inaccurate, and we won’t understand the actual effect of doubling CO2 until the diverse equilibrium assumptions are replaced by accurate dynamical assumptions.

So when the forcing from CO2 increases a watt or two, in an accurate model the clouds will emerge a few minutes earlier on average across the tropics, and the balance will be restored.

Maybe. I think it a good hypothesis, but I do not see good evidence one way or another. Compared to the natural variability in the TAO data, a few minutes earlier cloudiness on the days with the most downwelling long wave infrared is extremely difficult to detect.

Thanks Willis, I like the way genuine science is emerging from climatology, I commend you on your ability to explain your reasoning.
This is the mark of a true scientist, the ability and joy of explaining your knowledge so the average person might understand.
I too will have to devote some time this weekend to reread this post.

ferd berple: This is generally true in the tropics. Clouds form in the afternoon, more commonly during the wet season, then by morning the skies are clear.

To complement that, analyses of the TAO data by the curators showed that most of the rainfall occurs in the early morning hours. It is reasonable to hypothesize, following Willis, that the increase of CO2 will lead to earlier cloudiness, more (or earlier) net flow of water into the higher atmosphere, and perhaps more rainfall, with no net increase in the spatio-temporally averaged surface temperature.

‘Of everything’ returned Mrs Chick ‘Of course we must. It’s a world of change. Anyone would surprise me very much, Lucretia, and would greatly alter my opinion of their understanding, if they attempted to contradict or evade what is so perfectly evident. Change!’ exclaimed Mrs Chick, with severe philosophy. ‘Why, my gracious me, what is there that does not change! even the silkworm, who I am sure might be supposed not to trouble itself about such subjects, changes into all sorts of unexpected things continually.’

It’s quite true that chaotic systems vary, often in bistable alternations splitting at threshold levels, and are very difficult to predict. Hence it’s hard to predict the weather, or ENSO, more than a very short time ahead.

However, chaotic system variation is along the strange attractor for that system – while you cannot predict (without perfect information, never available) where the system will be within that attractor, it is limited to that attractor. We can look at _averages_, and describe the bounds of the attractor, and can predict that winters will be warmer than summers, that deserts will be drier than rain forests.

Another way of looking at this is to consider that weather is trend-stationary – when we have extrema, such as a storm, a drought, etc, the weather tends to return to the its average behavior afterwards. Which is entirely unsurprising, as short term variations are bounded by energy balances, and extra in/out leads to a later rebalancing. Again, short term behavior is very hard to predict in detail, while long term averages are much less so.

Weather concerns the short term chaotic behavior of interlinked non-linear systems. Climate concerns the long term _averages_ of those systems. Those averages are dependent on energy balance, on energy in versus energy out. And we can make contingent predictions on those – if we increase greenhouse gases, increase the greenhouse effect, reducing the energy radiating to space, then the energy in the climate will increase (warm) until that balance is restored. And during that the short term weather may change, as bistable divisions in behavior are crossed up/down.

“These cool the surface in a host of ways, most importantly by piping the warm surface air through the middle of the thunderstorm up to high altitudes. This avoids almost all of the greenhouse gases (H2O and CO2) in the lower troposphere, and allows for free radiation of huge amounts of thermal energy to space. ”

does not compute.
the warm surface air “piped” does not avoid H20 or C02.

Here we go again. Which bit of a thunderstorm shooting energetic molecules of H2O 20km into the atmosphere where they can radiate into space are you not following? At least try to engage in some meaningful way. Of course H2O is involved. Working fluid of the engine.

Working fluid of the engine in the sense of by-passing the GHE on the equator in a thunderstorm or making England warm in Winter when our weather comes from the SW (equatorial) or cold when our WV comes form the N or thereabouts. No GHE required – just H2O “doin’ its stuff.

Matthew R Marler says:
February 8, 2013 at 11:42 am
Frumious Bandersnatch: Clouds didn’t form anywhere with the same regularity during other parts of the year.

Same experience as mine in the Philippines and in Taiwan. I expect seasonal dependence of the effect of CO2 on cloud formation.
—————————————–
Matt, I was going to say basically the same thing about CO2 but I was going to add a /sarc tag.
cn

More appropriately in a discussion on chaos, chaotic behavior will exhibit bifurcations as some parameters change. This includes weather; changes in the strange attractors as conditions affect I should have used that terminology in my previous post – apologies, it’s been a while since I pulled Rasband 1990 (Chaotic dynamics of nonlinear systems) off the shelf…

Leo Smith to Willis: “By the way I do take issue with you denying it’s feedback. In a sense it is, because lower temperature water – rain and ice and snow – get fed back to the hot planet surface.”

Somebody please help me articulate this thought; I haven’t engaged in a sciency conversation about these things since I graduated many years ago so I may not even remember the correct terms. But I was left with the impression that the distinction between feedback and non-feedback systems was a mere formality and was more relate to the method of analysis rather than the process being described.

For example, where I grew up, we used to distinguish between feedback regulators and parametric regulators. A lavatory cistern would be an example of the former, and Zener diode, of the latter. Likewise, a Colpitts oscillator would be classed as feedback oscillator, while an oscillator built with a tunnel diode loaded with an inductance would be called parametric. In afterthought, I believe the distinction was based on the presence or absence of a dedicated feedback circuit with an analytical transfer function that could be assigned to it. With a Zener diode, or a tunnel diode, there was no such circuit, so you pretty much had to use an equivalent circuit with a tabulated non-linearity to model it (as opposed to a linear system with a rational right-hand side). I also remember such tabulated solutions were looked upon as inferior to the analytical ones (probably because they could not be solved by the pencil-and-paper method).

While reading Willis’s description of thunderstorms, the model I had in my mind was that of Zener diode (a.k.a. avalanche diode or breakdown diode), rather than a lavatory fill valve. If Willis is as old-school as I am, he would probably deny the existence of a feedback simply because there is no external driver that could be thought of as a dedicated feedback circuit.

In a sense, breaking down upon reaching a threshold is feedback; in some other sense, it isn’t. Am I making sense?

Gary Pearse says:
February 8, 2013 at 8:50 am
When the wet season came to this dry land, it was in the form of massive thunderstorms with torrential rain – all starting about 3 to 4 in the afternoon. If you were 100 feet from your door and the first drop of rain hit you, you would be drenched right through before you got inside. Often, it was accompanied by such a fall of hail that it would look temporarily like Saskatchewan in January out the window.

Classic monsoon, and the hail illustrates how high convection has to reach to produce precipitation. Monsoon weather and the descriptions of afternoon rain at Guam and other locations are essentially the same phenomena – just at different scales. Solar heating of the land surface produces convection, clouds and then precipitation.

The situation I was describing in Singapore is somewhat different. I believe what happens is that once a thunderstorm forms during the day, it can persist into the night, and even the next day, driven by its own internal processes. It no longer needs solar heating to drive it. I also believe higher humidity is the key difference between afternoon thunderstorms and thunderstorms throughout the 24 hours.

Just one question on your use of the concept of “emergent phenomenon” which may be a little different than I’ve heard it described in the past. It seems like you are using it to describe systems that are either too complicated or too poorly studied for us to understand how they work. In other words, there isn’t anything unusual about the chemistry and the physics involved, just that we don’t know enough to fully describe the process and predict the various changes in the system?

Or are you really focusing on the fact that there is a fundamental uncertainty — meaning, we literally *can’t* know — due, among other things to the uncertainty principle? What I mean by that is that climate is made up of wheather over time, which in turn is made up of masses of molecules and heat flow, which in turn is made up of individual molecule reactions (including the interactions of electrons), and due to the uncertainty principle (location vs. vector and velocity) it is ultimately impossible to predict how the innumerable molecule reactions will play out over time.

If the latter is true, then it would not just be a question of scientists working harder and gathering more data and inputting more paramaters and crunching more numbers. Rather, it would be a truly unknowable item.

KR says:
February 8, 2013 at 12:27 pmIt’s quite true that chaotic systems vary, often in bistable alternations splitting at threshold levels, and are very difficult to predict. Hence it’s hard to predict the weather, or ENSO, more than a very short time ahead.

However, chaotic system variation is along the strange attractor for that system – while you cannot predict (without perfect information, never available) where the system will be within that attractor, it is limited to that attractor. We can look at _averages_, and describe the bounds of the attractor, and can predict that winters will be warmer than summers, that deserts will be drier than rain forests.

There’s more to the role of chaos and nonlinear attractors than just making life difficult for weather forecasters. You cant hide chaos in the “short term” closet. Look at the Vostok and Greenland ice cores. It is very clear that glacial and interglacial states are alternate attractors, for every true interlgacial over the last couple of million years there have been dozens of abortive jumps, like a cat jumping to a branch but its claws not quite holding. It tries many times and every so often – as slow wavelike swaying of the branch from an external forcing wind (Milankovich orbital cycles) brings it periodically slightly closer to the ground, the cat gets into the tree.

This is what fractal means. Self similar pattern over ALL scales, whether temporal or spatial. Log-log distribution, events becoming logarithmically larger while they get logarithmically less frequent. The signature of nonlinear pattern formation.

Thus on longer timescales than out current glacial epoch (pleistocene) some interpret the temperature history of the whole phanerozoic (Cambrian to present) as being dominated by two alternate global temperatures – 12 (as now) and 20 C. This may be a gross smoothing but it would make sense – the same pattern over days, years, 10^4s and 10^8s of years.

I wondered if you could respond to the predictable ad hominem response from one individual.

Er, Mark. Isn’t it a bit much power to give this individual to ascribe something written in 1909 to be a response to a post Willis posted yesterday? Though there have been discussions of the graphs linked, it’s really not useful to bring them up on this thread.

Just one question on your use of the concept of “emergent phenomenon” which may be a little different than I’ve heard it described in the past. It seems like you are using it to describe systems that are either too complicated or too poorly studied for us to understand how they work. In other words, there isn’t anything unusual about the chemistry and the physics involved, just that we don’t know enough to fully describe the process and predict the various changes in the system?

Or are you really focusing on the fact that there is a fundamental uncertainty — meaning, we literally *can’t* know — due, among other things to the uncertainty principle?

You have hit the nail on the head – nail? what nail I hear you ask. Mister Essenbach has shown us that climate phenomena follow nonlinear emergent pattern. Yes, yes – this we have known all along, but where, you ask, does this lead us? Do we want to be taken where it leads us, Mister Anderson? Or do we just give up – that would be so easy, would it not, just say, Oh, its all so chaotic, there is nothing we can see into the future, delude ourselves that we can know what cannot be known, as if you yourself were the Oracle, Mister Anderson. Yes, I can see your thoughts turning already to her, your friend the Oracle and what will she tell you? I can tell you that, mister Anderson – she will tell you to find the program called Mister Doelman, a friend of the key-maker, he will give you a program called the Melnikov function. This is the only key to meaningful and predictive analysis of a weakly periodically forced nonlinear oscillator. Why am I telling you this, Mister Anderson? Why? Because chaos is the only friend you and I have in common, Mister Anderson.

“….The situation I was describing in Singapore is somewhat different. I believe what happens is that once a thunderstorm forms during the day, it can persist into the night, and even the next day, driven by its own internal processes. It no longer needs solar heating to drive it. I also believe higher humidity is the key difference between afternoon thunderstorms and thunderstorms throughout the 24 hours….”

This from http://www.guidemesingapore.com/relocation/introduction/climate-in-singapore is is agreement with you Philip… perhaps the forming of storms from warm seas/uprising air flows over land etc is complicated by other nearby land masses (Sumatra, Malay Peninsula, Riau Islands..)… also this equatorial island chain is unique in that all the globe circulating water flow from the Pacific Ocean piles up here and flows through this relatively shallow, extremely warm restriction…

Monsoon Characteristics

There is no clear-cut wet or dry season and rain is experienced every single month, usually in the afternoons and early evenings. However, there are two main monsoon seasons in Singapore: Northeast Monsoon Season (December-March) and the Southwest Monsoon Season (June-September).

…… Northeast Monsoon has a “wet phase” (December and January) and a “dry phase” (February and March). The wet phase witnesses continuous moderate to heavy rainfall in the afternoons and early evenings. The dry phase is cool and pleasant with comparatively little or no rain.

The Southwest Monsoon Season experiences showers and thunderstorm activity between predawn to midday. However, thunderstorms usually last for less than 30 minutes. ‘Sumatra squalls’ are common during this period. These are b>a line of thunderstorms that develop at night over Sumatra, move to the west coast of Peninsula of Malaysia and hit Singapore during the early morning hours. Heavy rain persists for 1-2 hours, followed by cloudy conditions and light rain until afternoon.

Steven Mosher says:
February 8, 2013 at 9:44 am
“These cool the surface in a host of ways, most importantly by piping the warm surface air through the middle of the thunderstorm up to high altitudes. This avoids almost all of the greenhouse gases (H2O and CO2) in the lower troposphere, and allows for free radiation of huge amounts of thermal energy to space.
does not compute.”
—————————————————————————-
Steven,
Willis’ calculation on this is correct. Willis is including all the things missing from the “basic physics” of the “settled science”. Gravity, atmospheric pressure gradient and the physical transport of energy by the movement of gases.

Gravity produces a pressure gradient in our atmosphere. This leads to an IR opacity gradient. This means that any atmospheric column is always radiating more IR to space than it is to the surface. Include the fact that the majority of the net energy flux radiative gases emit was not acquired through intercepted surface IR but through conductive flux from the surface and the release of latent heat. The release of latent heat is almost always above the level of maximum IR opacity. Almost none of it will return to the surface. Convection and particularly moist convection moves energy above the level of max IR opacity where its only escape route is to space.

Add to this the fact that without continued vertical convective circulation below the troposphere our atmosphere would dramatically heat and this vertical circulation depends on radiative cooling at altitude. There is only one answer, adding radiative gases to our atmosphere will not reduce its radiative cooling ability. Radiative gases cool our atmosphere at all concentrations above 0.0ppm

Quite simply the pseudo scientists that calculated that adding radiative gases to the atmosphere would reduce its radiative cooling ability never properly calculated the effects of Gravity, atmospheric pressure gradient and the physical transport of energy by the movement of gases. They did not just get the magnitude of the effect of additional CO2 wrong, they got the very sign of its effect wrong. What makes this so unbearably delicious is that in the age of the Internet, this failure to get the basic physics right is permanently recorded for all to see at the click of a mouse. An army of William Connellys cannot erase the shame.

If we are going to go there: All phenomena are emergent, (ephemeral too). They emerge, then they go bye-bye, laws of physics (long acting) and all. Some seem to stabilize/stratify for a bit (yin/night) longer than others (“laws”). (Impermanence has to be, otherwise some things would be permanent/fixed.) Thanks for putting this info up for us, and you are definitely on a roll. Thanks for looking around and reporting, Mr. E, reminding us all how we are supposed to be doing this humany thing.

May we return to unbiased awareness. This would have lots of benefits, so much more than saving the world from the harsh banal scientism of self proclaimed world saviors.

Read Willis’ other essays if you’re not sure about this one, then come back and reread.

To the guy who doubted that Willis could have written this: An open and inquiring mind is the most essential of scientific disciplines.

“These cool the surface in a host of ways, most importantly by piping the warm surface air through the middle of the thunderstorm up to high altitudes. This avoids almost all of the greenhouse gases (H2O and CO2) in the lower troposphere, and allows for free radiation of huge amounts of thermal energy to space. ”

does not compute.
the warm surface air “piped” does not avoid H20 or C02.

And why would it not avoid CO2 or H2O? Further, deponent sayeth not …

I do so wish you’d give up your cryptic one-sentence style of comments. The problem is that I have no idea WHY you think it is NOT the case that the GHGs are avoided. And as usual, you don’t say.

So let me go over it again. In the thunderstorm regime, the heat mostly moves from the surface to the LCL as water vapor due to the high evaporation rate under the thunderstorm. Since the radiation bands down in the mixing level are already totally saturated (75% of DLR striking the surface comes from the first 90 metres of atmosphere, 90% from the first 600 metres), this makes little difference to the radiative energy flow .

At the LCL the latent heat is converted to sensible heat, which reheats the air and keeps it rising through the middle of the thunderstorm tower. Inside the tower it is totally separated from the bulk tropospheric air, and does not exchange energy with it by conduction, convection, or by radiation. Everything is captured by the column of cloud. That is what I mean when I say it avoids contact with the GHGs and the CO2 in the lower troposphere.

At the top, the air emerges from the thunderstorm tower up towards the tropopause. Since the main bulk of the GHGs are in the lower troposphere, the warm air has gone around them all the way to the upper troposphere.

Now, if you have a problem with this explanation, I sure hope you have the nerve to defend your position. Because all too often, you make some cockamamie claim like this and just walk away. I’ve been wrong before, and on occasion you’ve been the one that has pointed it out. If I am wrong here, please have the courtesy to show me where.

Willis, excellent article. I presented it for discussion elsewhere, and though it is off-topic I wondered if you could respond to the predictable ad hominem response from one individual. It6 is a link claiming you ‘lied’. I would like to hear your take.

I haven’t read that hit piece in years. As I recall, the link claiming I “lied” is at Deltoid, the guy there is a bitter crab who hates me because I didn’t kowtow to him. Plus he’s a footnote to history and knows it, I think that’s why he’s bitter.

He didn’t like the way that I analysed Hansen’s predictions from 1988. It was a scientific discussion, not a question of lying, but he went all ad hominem on me. It happens, his blog gets maybe three hits a year, we get three million or some number like that, so I don’t worry about it.

People attacking me seems to be an entire cottage industry these days, which is great news, it means that I’m getting some traction.

Paul Martin says: February 8, 2013 at 5:33 am Verb sap… That Mauritz Escher drawing (used without acknowledgement) will still be under copyright.
……………………………………………………….
Paul, first name is Maurits. If you go looking for copyright claims, you will find more than one. It is easy to produce a sentence saying ‘Copyright (date) held by XYZ’.

“All copyrighted work published after 1978 is 70 plus the life of the author. That means that the copyright is good until the author dies, and then there is an additional 70 years. For works created prior to 1978, the rules get VERY complicated. This includes what year the work was created, what year it was filed with the copyright office, whether or not the author ever published the work, if they renewed their copyright, if they ever assigned the copyright to someone else, if the other person renewed them, if they died, if their heirs renewed the copyright, etc. ” That’s from USA circumstances at http://answers.yahoo.com/question/index?qid=20090605214636AAK1Fg8

Escher created this masterpiece in 1948. It is dated at identified on the original. Can you tell us its present copyright status, specifically doe Web use? Personally, I think it could have been drawn by a person other than Maurits Escher, but with the same name.

I find myself confused. I thought you were describing pretty clearly how thunderstorms locally increase heat radiation to space; but then you wrote that they increase throughput, which you defined as movement of energy towards the poles.

Does heat in the upper troposphere radiate poleward, rather than outward?

You said: “This is generally true in the tropics. Clouds form in the afternoon, more commonly during the wet season, then by morning the skies are clear.

There is also a vertical movement in the clouds. During the day the mountain tops are clouded, but at night they clear as the clouds descent and the sky overhead is crystal clear. The classic example is the Mona Loa observatory in Hawaii. Cloudy during the day, clear at night.”

I don’t disagree – but generally is not the same as doesn’t. After all, generally speaking thunderstorms are not the general state of weather even in the tropics.

@ Richard G

You said: “Cloud formation is a function of the temperature – dew point spread. When these converge clouds emerge. When they diverge clouds dissipate.”

I am aware of that; my question was that as daily low temperatures increase, is there the possibility of dew point spreads occurring more at night?

“If we are going to go there: All phenomena are emergent, (ephemeral too). They emerge, then they go bye-bye, laws of physics (long acting) and all. Some seem to stabilize/stratify for a bit (yin/night) longer than others (“laws”). (Impermanence has to be, otherwise some things would be permanent/fixed.)”

Exactly. Which is why I am trying to pin down exactly what is meant by emergent phenomena. It can’t be just that they “emerge,” otherwise everything is included and it becomes meaningless. It can’t be just that the system is too complicated for us to understand, otherwise emergent phenomena would no longer be emergent once we come to understand them. I do suspect, however, that Willis may be on to something in terms of things that “suprise” us. Perhaps emergence is just a label to attach to those phenomena that we don’t yet completely understand?

Ultimately it is all chemistry and physics, is it not? And if we knew enough about initial conditions (which may be impossible due, among other things, to the uncertainty principle), we would be able to predict with perfect clarity. Reminds me of the old and lengthy debate about whether there is such a thing as something actually happening by “chance.”

I find myself confused. I thought you were describing pretty clearly how thunderstorms locally increase heat radiation to space; but then you wrote that they increase throughput, which you defined as movement of energy towards the poles.

Does heat in the upper troposphere radiate poleward, rather than outward?

It does both, Duncan. Because it is up high it is able to radiate more freely … and what doesn’t get radiated away moves to the poles to be lost to space there.

Great article and great comments. I have always wondered how anyone could build a good climate model given the paucity of data and huge number of variables. As an engineer I worked with lots of rainfall, temperature, river flow, sun data, heating days etc. I used lots of “models” both dynamic and static, one dimensional and two dimensional, some “multi-dimensional”. The only thing I know, is with such a small number of years of data, it was always just a statistical “guess” as to the parameters to use. An educated guess, but nevertheless a guess. When you use a 200 year storm period projected from only one hundred years of data, you have no idea if a 200 hundred, 500 or 1000 year event has actually occurred in the data you used because the shapes of the curves vary by location.

And the focus so many have on temperature boggles my mind. Heat loss models have many dependencies, only one of which is temperature. I have an extremely well insulated house. I can model the heat loss for all sorts of conditions and design it appropriately. But even with a hundred or a hundred and fifty years of data, I can not predict what the maximum heat loss or gain will be over any given period or a trend. There are too many variables. For example, in my location, the average temperature for January in 2012 was -9.3 C; the average temperature this year was – 9.1 C The heating degree days were 5% higher in 2012 than 2013. BUT, the heat loss based on my metered water to water heat pump demand was 50% more in 2013 in 2012. Why. Less snow on the roof and around the foundations this year due to a few warm days melting it plus a lot more windy days – just as the heat loss models would tell you. But you can’t’ PREDICT anything with those models, just to what ifs.

I was never any good at solving multi-variable arrays, one of the reasons I didn’t go into structural engineering and stayed with nice easy things like modelling drainage basins, pipelines, water hammer, heat losses etc. Nice and simple. I can tell you what will happen if under certain parameters. I can’t predict WHEN an overloaded Terex truck will drive over a bridge that was designed only to carry unloaded ones, but I can pretty much tell you what the expected damage will be. Sort of like hurricanes. You can do damage assessment based on parameters, but you have a hard time predicting where, when and how strong.

Maybe it will be possible to build a huge multi-variable complex array that simulates our current climate one day. But I would not count on its predictions for even one year. Why – because there are too many unknowns that are significant. The uprising of one part of a continental plate, one large volcano exposing different minerals to the atmosphere can change everything. Some theorize that the oxygen we now breath is at least in part due to the exposure of carbonaceous materials during one such event and that weathering, chemical reactions and more access to carbon dioxide by the algae that were the predominant one celled life form at the time caused the increase in oxygen.

The modellers will always say that their results would have been correct if only …

For these and so many other reasons, I have a lot of trouble believing the current crop of climate modellers. Maybe someday there will be some models that can give reliable short term predictions, but probably not in the 10 or 20 years I have left to watch and enjoy the debacle.

Time to look outside and watch the horses play in the wind and snow and haul a load of hay.

“If we are going to go there: All phenomena are emergent, (ephemeral too). They emerge, then they go bye-bye, laws of physics (long acting) and all. Some seem to stabilize/stratify for a bit (yin/night) longer than others (“laws”). (Impermanence has to be, otherwise some things would be permanent/fixed.)”

Exactly. Which is why I am trying to pin down exactly what is meant by emergent phenomena. It can’t be just that they “emerge,” otherwise everything is included and it becomes meaningless. It can’t be just that the system is too complicated for us to understand, otherwise emergent phenomena would no longer be emergent once we come to understand them.

Thanks, guys, for pointing to an issue I obviously need to clarify.

First, there is no bright line between emergent and non-emergent phenomena. Identifying them depends on their having most or all of the characteristics I listed in the head post, viz:

So those are some of the characteristic features of emergent phenomena. They are flow systems far from equilibrium which arise spontaneously, often upon crossing a critical threshold. They are not obviously predictable from the underlying conditions. They move and act unpredictably, they are often associated with phase changes, and they exhibit “overshoot” (hysteresis).

Since not all phenomena have those particular characteristics, I fear it is not correct to say “All phenomena are emergent, (ephemeral too).”

Next, note that by “surprising” phenomena I did not mean “the system is too complicated for us to understand”. Instead, I described it as “not obviously predictable from the underlying conditions”.We understand how a termite builds its mounds, we can see why the ventilation shafts go the way they go to keep the colony from cooking in the hot African sun. Understanding is after the fact.

“Surprising” means that a person who has never seen a termite mound or a termite would never look at a few of them wriggling around and think “I bet they build giant houses with special ventilation channels”. Termite mounds would have certainly surprised the first Europeans to see them, for example …

Note also that the mound has a lifetime that is relevant in the timespan of interest. Note that the lifespan of the emergent climate phenomena ranges from minutes (dust devils) to multi-decadal (PDO) and perhaps longer. In the termite mound example, there was a time when that mound did not exist. At some point it will cease to exist. (Yes, I know that even the universe has a lifetime … but that doesn’t mean that we see emergent phenomena in a block of steel.)

In any case, no, not all phenomena are emergent. That was the point I made in the head post by comparing a system with just a bar of steel to a system with clouds and thunderstorms.

Indeed, another name for emergent phenomena is “self-organized phenomena”.

Another key to recognizing emergent phenomena is that they arise spontaneously when conditions are right. They don’t have to be artificially generated. They create themselves in response to external stimuli.

That last I am not so sure about. FWIW, I perceive them as patterns that normally are random, but that within the randomness is/are fluctuations that sometimes “get in phase” as some factor increases up to and beyond an “in-phase” point, lending structure to them while the variations are within a narrow band, then recede after the phase (literally) has passed.

A new type of clouds, literally,called undulatus asperatus appear to be organized in a way that looks like some intelligent design. (See http://en.wikipedia.org/wiki/File:Beautiful_clouds.JPG) I have seen these myself and photographed them, though my photos don’t show them as well as they might have. The ones I saw were barrel-vaulted, with one barrel vault next to another, in a pattern over 10 miles wide and who knows how long the whole pattern was. Each one was roughly 200-300 yards wide. I attribute them to an uncommon in-phase condition in the atmosphere under them. I’ve fairly often seen high-altitude parallel lines of clouds, and I think those and these were related – somehow, sometimes it seems the underlying layer of clouds form long series of waves that do not get broken up by turbulence, and the randomness of cloud patterns changes and they then appear non-random. (BTW, the clouds I saw were not noticed by the local weathermen to my knowledge, since I saw nothing on the Chicago weather news about it.)

I won’t claim that flocks of birds and fishes are similarly attributable. Those I assume move “as one” due to some group intelligence/mind that has not yet been discovered yet (most probably because we have not gone looking for it, perhaps because the current Reductionist paradigm doesn’t allow for it). The idea of mind=brain is too well ingrained for scientists to conceive a mind that spans across more than one single organism. We perceive cells to only be organized within a single organ or organism, but don’t allow that individual organisms/fauna might in themselves be cells of a larger intelligence. Reductionism also dictates that the thing we call “instinct” cannot possibly be genetically inherited memories. Instead we explain, e.g., migrating birds’ navigation by tiny bits of magnetic material in their brains: We HAVE to find an explanation within the Reductionist model – otherwise it is relegated to mumbo-jumbo metaphysics and then ignored. (Besides, I lived for decades in a migratory “highway”, and [literally] almost all of the flocks of geese I ever saw were not flying south or north, but in some skewed direction; this led me to discount any idea of internal compasses, because why would they head WSW or ESE in the fall, instead of straight south? – a compass should send them in one single direction, not all over the place as I’ve seen.)

But maybe there isn’t any mumbo-jumbo to it. Maybe we are overlooking better explanations because we are wearing Reductionist blinders. Maybe Reductionism isn’t the end-all and be-all of scientific inquiry. Maybe there really are organizing principles at work.

I much prefer the alternate term you use, Willis – “self-organizing phenomena” – to “emergent phenomena” because “self-organizing” is more relevant. “Emergent” suggests “newly born.”

emergent1. emerging
2. arising unexpectedly or as a new or improved development
3. recently founded or newly independent: an emergent nation

I can see that you are choosing the more vague “arising unexpectedly” meaning, but I don’t really agree with that. I had missed this post and could not figure out in your next post just what you were referring to. There is “emerging” about flocks of birds moving together or termites building towering hills for homes? Nor about a quasi-cyclical ENSO or PDO or AMO, phenomena which apparently have been around for a very long time? You are choosing “emergent” because the phenomena are arising from the background noise – but isn’t that true of all discoveries in science?

I DO LIKE where you are going with this, though, Willis, even if I take a slightly different view of it all. Seeing undulatus asperatus clouds over an area of a hundred square miles or so suggests in a real world way that patterns do sometimes emerge in what looks organized – and may actually BE organized, even if only for a while. Some of them we need to pay attention to, also (e.g., ENSO, AMO, PDO). But since some of them come and go (some in an almost regular temporal pattern), but not ALL (some like termite hills are built by intent), I would suggest there are two subcategories, if not more. I wouldn’t put ENSO with termite hills or flocks of birds, for example.

@feet2thefire: Sorry to intervene; I realise your message is addressed to Willis, but I just want to throw in a couple notes and retire for the night.

> A new type of clouds, literally,called undulatus asperatus appear to be organized in a way that looks like some intelligent design

Interesting clouds, and I agree somewhat unusual, but I don’t see anything intelligent about them. No more intelligent than sand dunes or snowdrift, and if you decant two immicible fluids into a glass and give it a jolt, you will see a pattern like this at the interface.

> We perceive cells to only be organized within a single organ or organism, but don’t allow that individual organisms/fauna might in themselves be cells of a larger intelligence.

> Reductionism also dictates that the thing we call “instinct” cannot possibly be genetically inherited memories.

This is the first time I hear about “Reductionism”. If you didn’t invent it and it has a following, I can assure you no such belief is popular in biology. For a biologist, “instinct” means “programmed behaviour”. That’s just a short way for referring to any behaviour we inherit — nothing precise.

> Besides, I lived for decades in a migratory “highway”, and [literally] almost all of the flocks of geese I ever saw were not flying south or north, but in some skewed direction; this led me to discount any idea of internal compasses, because why would they head WSW or ESE in the fall, instead of straight south?

I could tell where you lived without you mentioning Chicago, just based on the directions you named. You are talking about Canada geese, the golf course pests. What made you think they ought to go straight south? What’s in the south that would attract you if you were a flock of geese? Canada geese in the Midwest roam on the fringe of snowmelt when there is snow on the ground (don’t ask me why; I don’t know — but I will appreciate if somebody can enlighten me). In the absence of snow, they don’t migrate. They come back to the Great Lakes area to breed when the chances of snowing become slim, then remain in the general vicinity of their breeding ground as long as there is grass to graze. As soon as there is snow on the ground, they depart WSW. They go to the West Iowa – Nebraska – Oklahoma area where they are apparently not as happy, because as soon as the snow in the Lakes area melts, they are back. How do they know? Beats me, but I think they have the same or better weather forecasting ability as our meteorologists, at least as far as the weather patterns in the Midwest are concerned. They always depart when they can no longer reach the grass through the snow cover, but not immediately. They wait two or three days to make sure the condition is stable. If the snow begins to melt, they stay. If the ponds freeze, they depart sooner. Likewise, they return within days following the onset of substantial snowmelt, and they usually return from the same direction where they disappear.

I was so curious I took a few trips out just west to check on them. Always found them either there or near the Lakes; never at both places in the same time.

I think if your sampling rate were higher (I watched them every day for years), you would detect the same pattern.

I much prefer the alternate term you use, Willis – “self-organizing phenomena” – to “emergent phenomena” because “self-organizing” is more relevant. “Emergent” suggests “newly born.”

emergent
1. emerging
2. arising unexpectedly or as a new or improved development
3. recently founded or newly independent: an emergent nation

I can see that you are choosing the more vague “arising unexpectedly” meaning, but I don’t really agree with that.

First, when a cumulus cloud pops out of a perfect blue tropical sky, in what sense is it not newly born?

Second, you’ve given the dictionary definition. Emergent phenomena are a well recognized field of study, and like all such specialized fields, they use particular words as “terms of art”, meaning that they have particular or slightly different meanings than the common meaning. No good me or you complaining because people use words funny in specialized subjects.

Finally … “emergence” is the usual term employed by everyone discussing the subject. You may find theoretical problems with that use of the word, you may not like that usage, but that’s how it’s used, so that’s how I use it. Wikipedia, that font of dubious information, says:

Emergence
In philosophy, systems theory, science, and art, emergence is the way complex systems and patterns arise out of a multiplicity of relatively simple interactions. Emergence is central to the theories of integrative levels and of complex systems.

Looks like they already took the vote, and ’emergence” won, and you and I didn’t even get a ballot …